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INTRODUCTION
First of all, before I even begin, please take a few moments to watch the funniest video I can ever remember having seen: My apologies if linking to a Hitler parody offends anyone, but sometimes funny is just funny. : ) Moving right along, it is my hope that this essay is useful and informative in explaining the differences between formats (sensor sizes), and what role both the sensor and glass play in terms of image quality (the section on IQ is a "must read" to keep the discussion of the technical in perspective). The two single most important concepts in this essay are to make the distinction between aperture and f-ratio as well as the distinction between exposure, apparent exposure, and total light. Confusion of the meanings of these terms, and the importance of making the distinction between them, is the number one reason so many have difficulty understanding the concepts presented here. However, what this essay does not discuss in detail are the operational differences between systems which often play a far more important role than IQ alone in determining which system is better for a particular photographer. The impatient reader may wish to skip ahead to the section on The Purpose of Equivalence for the thesis of this essay. Speaking of impatience, some have scoffed at the structure and length of this essay: http://forums.dpreview.com/forums/read.asp?forum=1022&message=30362233 "Well, it's a link to something badly structured, a long text mass I am not really interested to spend time on. I guess if it can't be explained in a few short sentences then it can't be that important. IMO it is pointless to compare ISO6400 images with ISO1600." As for being "badly structured", I apologize if the index and "topic boxes" don't work for some, but it is not necessary to read the whole essay straight through. While the topics are all related, you may simply use the index and click on topic(s) of interest. However, I have no answer for the line "I guess if it can't be explained in a few short sentences then it can't be that important." I understand that many live in a society of "instant gratification" and that it may be frustrating to have to actually read more than a few sentences to understand a subject. Nevertheless, there do exist concepts that can't be explained in a few short sentences, including why it sometimes makes sense to compare an ISO 6400 image to an ISO 1600 image. However, whatever the differences in IQ may be, please keep in mind this key point when debating the IQ differences between systems: do you take photos where the IQ differences between systems make any difference at all to your target audience for the types of photos you take and the skills that you have?
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Q&A
This section is a "quick and dirty" session where many misconceptions about the differences between systems with different formats are addressed. All these points are addressed in more detail in other sections of the essay. Before beginning the Q&A session, I'd like to make an analogy between camera systems with cars. We can think of sensor size as engine displacement, lens speed as engine RPMs, and lens quality as the tires. For example, if an engine with a smaller displacement revs faster than an engine with a larger displacement it does not necessarily follow that it puts out more power. Likewise, if one engine has more power than another, it does not necessarily follow that it has more acceleration unless the tires can deliver that power to the pavement. But regardless of which vehicle outperforms which in which circumstances, the question is always if the driver has the skills to make use of that power. This is no less true with photography. Even given that the equipment is capable does not give us any sense that the photographer can make full use of that potential, or that the differences will be meaningful for how the equipment is used. Of course, just how much of a difference constitutes "meaningful" depends on the photographer or, perhaps more accurately, the target audience (which, in many cases, is the photographer!). For example, a Corvette will smoke a minivan in almost every conceivable race, but the minivan is simply the better tool for the job for many people. Or, even more to the point, one car may have a laptime of 72.34 seconds, and another a laptime of 69.71 seconds, which is an eternity in an actual race, but meaningless for "real life" use of the vehicle. Likewise, one camera system may have higher IQ than another, but this does not necessarily mean it's the best system for the job at hand for a particular photographer, nor does it necessarily mean that the differences in IQ between systems makes any meaningful difference for the end product to the target audience. In the end, we must consider the system as a whole, both in terms of IQ and operation, and in conjunction with our needs, skills, and audience. That all said, let's begin the Q&A: Q: What is the purpose of Equivalence? Q: Isn't the real purpose of Equivalence
to stack the deck against smaller sensor systems and promote FF? Q: What are the advantages of smaller sensor systems? Q: What are the advantages of a larger sensor system? Q: Why do larger sensor systems usually offer
more IQ? Q: Isn't the reason that larger sensor
systems have less noise because they have larger pixels? Q: But don't larger sensor systems require sharper glass? Q: What do you mean when you say "the lenses
for larger sensor systems usually have larger apertures for a given AOV"? Q: But f/2 results in the same
exposure regardless of the format, right? Q: Don't smaller sensors have more DOF than larger
sensors? Q: Won't larger sensor systems lose their
noise advantage when they up the ISO to match the DOF and shutter speed of
smaller sensor systems? Q: Won't larger sensors suffer diffraction softening earlier than smaller
sensors when stopping down for the same DOF? Q: But don't larger sensor systems have softer corners
and more vignetting than
smaller sensor systems? Q: Don't smaller sensor systems have more reach?
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DEFINITIONS OF TERMS AND ABBREVIATIONS
Many of the misunderstandings come from people using different definitions for the same words. In particular, "f-ratio" is often confused with "aperture", and "exposure" is confused with "apparent exposure" and "total light". The importance of these distinctions is often overlooked or simply not understood, so a quick browse through this section would be helpful in understanding the rest of the essay. IQ: Image Quality AOV: Angle of View Perspective: The relative position of objects in the frame (a function only of subject-camera distance -- format and focal length independent)
Exposure: The product of the intensity of the light and the time the shutter is open: Exposure = Intensity x Time
Diffraction Softening: Detail lost due to the diameter of the Airy disk exceeding the diagonal of a pixel due to the wave nature of light
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DEFINITION OF "EQUIVALENCE"
Equivalent images are images from two different cameras that share the following five parameters below. It is critical to note that "equivalent" does not mean "equal" -- I cannot stress this point enough. That said, the definition of "equivalent images" is as follows: 1) Same Perspective Understanding the fundamental concepts of Equivalence requires making important distinctions between various terms which people often take to mean the same thing. It is very much akin to making the distinction between "mass" and "weight", two terms which most people take to mean the same thing, when, in fact, they measure two different (but related) quantities. While there are circumstances where making the distinction is unnecessary, there are other times when it is critical. The first of these distinctions that needs to be made is between aperture and f-ratio. The aperture is the apparent diameter of the opening in a lens as viewed through the front element, whereas the f-ratio is the quotient of the focal length of the lens and the aperture, or, equivalently, the aperture is the ratio of the focal length and the f-ratio. For example, a 50 / 1.4 lens will have a maximum aperture of 36mm since 50mm / 36mm = 1.4. Likewise, we can say a 50 / 1.4 lens has a maximum aperture of 36mm since 50mm / 1.4 = 36mm. The aperture, together with the shutter speed, determines the total amount of light that falls on the sensor, and, in combination with the perspective and focal length, determines the DOF (for a given display size, viewing distance, and visual acuity). This naturally brings us to the distinction between total light, exposure, and apparent exposure. The total light is simply the total amount of light that falls on the sensor, and is a function solely of the aperture and shutter speed for a given scene, perspective, and framing. The exposure, on the other hand, is the intensity of the light falling on the sensor, which is a function of the f-ratio rather than the aperture. Since equivalent images are made from the same total amount of light, the light falling on the larger sensor will have a lower intensity (lower exposure) than a smaller sensor, just as a force applied over a larger area exerts less pressure than the same force applied over a smaller area. To compensate for the lower exposure, the larger sensor system needs to use a higher ISO to amplify the image to get the appropriate level of brightness (apparent exposure). It is important to note that the definition of equivalence, per se, does not discuss elements of IQ, such as detail, sharpness, noise, vignetting, color, bokeh, etc., but that this essay does discuss the role that sensor size plays in IQ. In particular, it is important to recognize that "same noise" is not a postulate of equivalence, but instead a consequence of equivalent images if the sensors have the same efficiency and the images are compared at the same level of detail (discussed more thoroughly in the Noise section of the essay). The FM ("focal multiplier" -- more commonly referred to as the "crop factor") is the vehicle by which we compute equivalent settings for different formats. For the same AOV, the FM is the ratio of the diagonal of the larger sensor to the diagonal of the smaller sensor. If the aspect ratios (the ratio of the length and width of the sensor) are the same for the two systems, then the FM for the same AOV will be the same as the FM for the same framing as well. However, if the aspect ratios are different, we will need to frame wider with one system, and then crop to the same framing as the other. In this instance, we compute the FM as the ratio of the smaller dimensions of the sensors if cropping the more elongated image to the aspect ratio of the more square sensor, or the ratio of the longer dimensions of the sensors if we are cropping the more square image to the aspect ratio of the more elongated sensor. It's often convenient to express the FM in stops and then round to the nearest 1/3 stop: FM (in stops) = 2 log2 FM (when rounding, it's helpful to recall that 1/3 ~ 0.33, and 2/3 ~ 0.67). Let's demonstrate this by working some examples between 35mm FF (24mm x 36mm, 43.3mm diagonal) and 4/3 (13mm x 17.3mm, 21.6mm diagonal): Same AOV: FM = 43.3mm / 21.6mm = 2.00 (2 stops) To calculate equivalent settings, we multiply the FL (focal length) used by the smaller sensor system by the FM to get the FL for the larger sensor system that will give the same AOV (or FOV, depending on how we choose to compute the FM). Similarly, we multiply the f-ratio of the smaller sensor system by the FM to get the f-ratio for the larger sensor system for the same DOF, and the ISO used by the smaller sensor system by the square of the FM to get the ISO for the larger sensor system that will give the same shutter speed for the same apparent exposure. Alternatively, adding the FM (in stops) to both the f-ratio and ISO is usually preferable to the "messy" multiplication. Let's work some examples to demonstrate: 25mm f/2 ISO 100 on 4/3 has the same AOV as 50mm (25mm x 2.00), the same aperture as f/4 (f/2 x 2.00 = f/4), and the same shutter speed as ISO 400 (ISO 100 x 2.00² = ISO 400) on FF. However, while we need to perform the multiplication to get the focal length, it is often easier to instead add the FM in stops for the f-ratio and ISO: f/2 + 2 stops = f/4, ISO 100 + 2 stops = ISO 400. Similarly, we could use an FM of 1.85 (1 2/3 stops) and get the settings required on FF if we were going to crop the FF image to the same framing as the 4/3 image, and use an FM of 2.08 (2 stops) if we were going to instead crop the 4/3 image to the same framing as the FF image. Since the most common aspect ratios, by far, for digital cameras are 3:2 and 4:3, we can see that the practical differences in the FM between the AOV and FOV differ by less than 1/3 of a stop, so it is not a significant factor in terms of total light gathered, and thus noise. In addition, 1/9 of the pixels will be cropped away from the edges, which will have negligible impact on the PPI of a print, but may be important in terms of comparing corner sharpness. The last step in making the images "equivalent" is to crop to the same framing, and either resample the images to the same output size if comparing on a monitor (usually at least as large as the larger size image, but not necessarily so), or print at the same dimensions if comparing prints.
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THE PURPOSE OF EQUIVALENCE
The motivation behind this essay was to dispel common myths about different formats which all sprang from one central fallacy: to compare systems at the same f-ratio. On the other hand, "equivalence" holds that there is not one parameter, but five, which are central to photography: 1) Perspective An equivalent image is an image where all five of these parameters are the same. As noted in the definition of equivalence in the section above, elements of IQ, such as detail, sharpness, noise, vignetting, color, bokeh, etc., are not included in the definition since "equivalence" does not mean "equal", nor is it a mandate on how to use systems. Furthermore, it is important to recognize that "equivalence" does not make any claims about which system is "better", as what constitutes "better" is entirely subjective, and involves operational considerations (size, weight, price, focus speed/accuracy, etc.) that are not addressed by equivalence (see the Q&A section for more on this). Instead, equivalence is a set of parameters that serve as a starting point for comparing the IQ of systems. However, it often makes more sense to compare the IQ between systems at non-equivalent settings (discussed in the section immediately below) to maximize the IQ of the system being used. One of the most common situations where it makes sense to compare images that are not fully equivalent is when there is no need for the shutter speeds to be the same. These types of images usually occur whenever a photographer is able to remain at base ISO and still maintain a "sufficient" shutter speed to avoid motion blur and/or camera shake, as well as an "appropriate" DOF for the scene. Another scenario is the exact opposite -- to compare images at the same shutter speed and ISO rather than the same shutter speed and DOF. This type of comparison is useful when image noise and motion blur / camera shake play a more central role in the IQ of the image than do either DOF or corner sharpness. Another common scenario where fully equivalent images are not the "best" way to compare is when the photographer using a larger sensor system is focal length limited by the available lenses, and will compare systems at the same focal length and crop the image from the larger sensor system to the same framing as the smaller sensor system. On the other hand, sometimes the entire point of a comparison is to compare images at the extreme limits of the equipment, such as at their minimum DOFs, maximum apparent magnifications, minimum focus distances, etc. Lastly, we sometimes may compare images at settings that are not fully equivalent to make use of an operational advantage, such as intentionally dragging the shutter and making use of IS (either in-lens or in-camera) to create an artistic motion blur while maintaining a sharp background for pics where a tripod is impractical. But it makes no sense to stage a comparison with settings that artificially handicaps one of the systems. The most common scenarios for this are when systems are compared at the same f-ratio rather than the same DOF when comparing corner sharpness, or comparing images at the pixel level when one image has significantly more pixels than the other, or comparing noise at different levels of detail. Lastly, although not a postulate of equivalence, comparing hardware on the basis of in-camera jpgs is a poor way to compare the potential of the equipment. While it may be the most appropriate method of comparing for people who do not shoot RAW, it is hardly indicative of what the systems can achieve, in terms of IQ. The point of photography is making photos. As such, one doesn't choose the particular system to get images which are equivalent to another system. A person chooses a particular system for the best balance of the factors that matter to the them, such as price, size, weight, IQ, DOF range, available lenses, and/or operation. By understanding which settings on which system create equivalent images, the difference in their capabilities is more easily understood. For example, a 50 / 1.4 on 35mm FF is equivalent to a 31 / 0.9 on 1.6x or a 25 / 0.7 on 2x, neither of which exist, and would be a reason for one person to choose a 35mm FF system if they needed such a lens. On the other hand, a 4/3 system can get you a DSLR and a lens with an EFL of 28-84mm for less than the cost of the most inexpensive FF DSLR body alone. Even more extreme, are compact digicams, such as the Canon G10, which deliver an EFL of 28-140mm (albeit having an effective minimum DOF from f/13 - f/21), and have, according to some, IQ as good as medium format for certain situations (please take a read of this article). The five parameters of Equivalence are simply guidelines to comparing systems in a fair and appropriate manner, and are not a mandate that systems must be compared in such a fashion. However, when comparing anything but equivalent images, it is prudent to understand under what circumstances the comparison is valid. For example, we cannot make the blanket statement that FF has less noise than smaller formats, because the only way for FF to make good on this claim is in circumstances when it can use a slower shutter speed or a more shallow DOF. If these sacrifices are not possible, then such a claim cannot be made (for the same efficiency sensor). We choose one system over another on the basis of size, weight, operation, available lenses, IQ, DOF range, and, of course, price, so it is important to understand that IQ is only factor in determining which system is the best tool for the job. How each person weighs the options will dictate their own unique choice for which system is best for their needs.
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EQUIVALENCE AND PARTIAL EQUIVALENCE
As discussed in the section above on the Purpose of Equivalence, there are many times when we would not compare systems at fully equivalent settings -- "equivalence" is merely the baseline for a fair comparison between systems. Let's compare equivalent settings for the Canon 5D (35mm FF), Nikon D300 (1.5x), Canon 40D (1.6x), Olympus E3 (4/3). The FM between the 5D and D300 is 1.5 (for both the same AOV and FOV, as they have the same aspect ratio of 3:2), the FM between the 5D and 40D is 1.6 (again, for both the same AOV and FOV), and the FM between the 5D and E3 is 2 (for the same AOV only as the E3 has an aspect ratio of 4:3). Below are examples of equivalent settings (rounded to the nearest 1/3 stop) which means that for the same perspective (subject-camera distance) and display dimensions, they will have the same AOV and DOF. If the shutter speeds are also the same, they will have the same apparent exposures, as well. However, the level of detail will depend on the pixel count of the sensor and the sharpness of the lenses used, and the level of noise will depend on the efficiency of the sensor (although, typically, for a given generation of camera and at the same level of detail, the noise levels will generally be very close for equivalent settings). So, that all said, let's take a look at some fully equivalent settings on different formats: 1) 5D at 80mm, f/8, 1/200, ISO 400 For equally efficient sensors, the differences in IQ between the systems will be at a minimum. As always, which system has the "IQ advantage" will be a subjective measure, but most likely will go to the system that is able to render the greatest amount of detail, which will often be the system that has the largest native pixel count (discussed in more detail here). Sometimes, we can get away with a slower shutter speed, rather than a higher ISO, and thus have lower noise for the formats that are able to use lower ISOs. The following comparisons are examples of partial equivalence where shutter speed is traded for ISO in the larger sensor systems, which will allow them to obtain a cleaner image with more detail (pixel count and lenses permitting) while still maintaining the same AOV, DOF, and exposure: 1) 5D at 80mm, f/8, 1/50, ISO 100 Note the "danger" in comparing partially equivalent situations -- the lower shutter speed used to maintain the lower ISO will not always be feasible due to motion blur and/or camera shake. This can even be taken in the opposite direction when one system has in-camera IS and/or in-lens IS that the other system does not. Other times, we might rather use a more shallow DOF than a lower shutter speed to use a lower ISO and thus less noise, either because we prefer a more shallow DOF, or we need a fast shutter but lower noise is more important than the "side effects" (softer corners and more vignetting) of a more shallow DOF, but still the same AOV, shutter speed, and exposure: 1) 5D at 80mm, f/4, 1/200, ISO 100 Some may have noticed that the D300 and 40D use the same f-ratio and ISO, but slightly different FLs. The reason is that all numbers are rounded to the closest 1/3 stop, and the difference between FMs of 1.6 and 1.5 produce is less than 1/3 of a stop. The same type of minor correction for FL will happen if framing and cropping the 4:3 images to 3:2 or framing and cropping 3:2 to 4:3, but will be too small to see an effect on the f-ratio or the ISO. Lastly, as noted a bit further up, it is important to note that systems with in-camera IS will often enjoy a distinct advantage over systems without in-camera IS, or IS lenses in the desired focal range, for handheld shooting of static scenes or handheld shooting where motion blur is a desired artistic effect.
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THE FIVE POSTULATES OF EQUIVALENCE PERSPECTIVE Perspective is how objects appear in relation to other objects. It is a function only of the distance of the camera from the subject. Technically, it is a function of the distance from the subject to the lens aperture, but as long as we are not at macro, or near macro, distances, it is sufficient to think of the perspective simply as the subject-camera distance since this amounts to a difference of only a few inches. Two photos taken from the same position will have the same perspective regardless of the focal length or sensor size regardless of the FL (focal length) of the lens used.
FRAMING For a given perspective, the framing can be thought of as the whole of the captured scene, and can be expressed as the FOV (field of view), which is the width and height of the scene measured on the focal plane. The AOV (angle of view), on the other hand, gives the diagonal angle of the captured scene on the focal plane, which, interestingly enough, depends on the perspective. That is, depending on the subject-camera distance, the AOV changes even for the same focal length, but insignificantly so for non-macro distances. A quick example of these concepts is to consider a portrait of a person on the beach standing 10 ft away using a 50mm lens on a 35mm FF camera. The FOV for the scene would then be 7.1 ft x 4.7 ft (even though the background may stretch for miles) with an AOV of 46° (as opposed to the 47° that the lens would have at infinity focus, giving an EFL of 51mm). Both the AOV and FOV are functions of the perspective (distance to subject), the sensor size, and the focal length of the lens but the FOV also takes into account the aspect ratio of the captured image. Since the two most common aspect ratios, by far, are 3:2 and 4:3, in practice it is often sufficient to compare IQ on the basis of AOV rather than FOV, since the 3:2 rectangle is only 4% wider and 7.5% shorter than a 4:3 rectangle with the same AOV. However, there are situations when it makes more sense to compare with different AOVs cropped to the same FOV, such as when corner sharpness is of supreme importance. Being well aware that math is a major turn-off for many people, you may click here to jump to the next section. For those that have decided to stay, let's begin by defining a few variables to make the formulas less cumbersome, followed with the formulas and some examples on four different formats (FF, 1.5x, 1.6x, and 4/3) and the two most common aspect ratios for digital cameras (3:2 and 4:3): d = distance to subject (mm) We can now compute the AOV for rectilinear lenses at non-macro distances: AOV = 2 · tan-1 [ s · (d - FL) / (2 · d · FL) ] which can be reduce to Alternatively, we can express the AOV as a function of the magnification where the magnification (m) is approximated by: m ~ FL / (d - FL): AOV = 2 · tan-1 { s / [ (2 · FL) · (1 + m) ] } For infinity focus, both of these formulas can be reduced to: AOV = 2 · tan-1 [ s / [ (2 · FL) ] Solving for focal length, we have: FL = (s · d) / [ s + 2 · d · tan (AOV / 2) ] or, for infinity focus, FL = s / [ 2 · tan (AOV / 2) ] This means that the effective focal length (EFL) of the lens for a subject at a distance d (mm) is given by: EFL = (d · FL) / (d - FL) Let's compute some examples for infinity focus (m=0), which is the AOV that manufacturers give for a lens: AOV for 50mm on FF = 2 · tan-1 [43.3mm / (2 · 50mm)] ~ 47° Next, let's repeat for a subject at 3 ft (914.4mm): AOV for 50mm on FF = 2 · tan-1 [ 43.3mm · (914.4mm - 50mm) / (2 · 914.4mm · 50mm) ] ~ 45° This means that the EFL is (914.4mm
· 50mm) / (914.4mm - 50mm) ~
53mm. Below is a table to show the effect of subject distance on the
EFL for a 50mm lens:
FL = 43.3mm / [ 2 · tan (47° / 2) ] = 50mm or, alternatively, for an AOV of 45° for a subject at 3 ft (914.4mm) on a 4/3 sensor: FL = (21.6mm · 914.4mm) / [ 21.6mm + 2 · 914.4mm · tan (45° / 2) ] = 25mm. The FOV, on the other hand, is a bit more complicated than AOV, as it gives two measurements: one for the width of the scene, and the other for the height. In addition to the focal length and sensor diagonal, we need to know both the aspect ratio and the subject-camera distance to calculate the FOV (and will ignore magnification corrections). As before, let's begin by defining some variables to make the formulas easier to read: r = sqrt (a² + b²) where the aspect ratio of the sensor is
a : b Calculate c: c = s · (d - FL) / (r · FL) We can also find the focal length used for a scene if we know the actual width or height of the scene. If we let "w" be the width of the scene (in mm) and "h" be the height of the scene (in mm), then for an aspect ratio of a : b, where "a" corresponds to the width of the scene, and "b" corresponds to the height, we have: FL = (a · s · d) / (a · s + r · w) or, using the height of the scene instead of the width, FL = (b · s · d) / (b · s + r · h) So, once again, let's do some examples. The FOV for a lens at 50mm and 10 ft from the subject using a 35mm FF camera with a 3:2 aspect ratio, is computed as follows: r = sqrt (3² + 2²) ~ 3.6 Calculate c: c = 43.3mm
· (3048mm - 43.3mm) / (3.6 · 50mm) ~
723mm ~ 2.37 ft. Alternatively, if a 3:2 scene captured with a 35mm FF sensor from a distance of 10 ft (3048 mm) has dimensions of 7.1 ft (2164mm) x 4.7 ft (1433mm), we can compute the focal length used: FL = (3 · 43.3mm · 3048mm) / (3 · 43.3mm + 3.6 · 2164mm) = 50mm or FL = (2 · 43.3mm · 3048mm) / (2 · 43.3mm + 3.6 · 1433mm) = 50mm. Next, we'll repeat computing the FOV for 1.5x, 1.6x, and 4/3, but skip further examples computing the focal length from the scene dimensions. So, repeating for a 1.5x camera with the same perspective, AOV, and aspect ratio, we have: r = sqrt (3² + 2²) ~ 3.6 Calculate c: c = 28.4 mm
· (3048mm - 28.4mm) / (3.6 · 33mm) ~
722mm ~ 2.37 ft. And now for a 1.6x camera, once again with the same perspective, AOV, and aspect ratio, we have: r = sqrt (3² + 2²) ~ 3.6 Calculate c: c = 26.7 mm
· (3048 mm - 26.7mm) / (3.6 · 31mm) ~
723 mm ~ 2.37 ft. Finally, we will compute the FOV for a 4/3 camera (4:3 aspect ratio) for the same perspective and AOV: r = sqrt (4² + 3²) = 5 Calculate c: c = 21.6 mm
· (3048mm - 21.6mm) / (5 · 25mm) ~
523mm ~ 1.72 ft. Note that the FOV for the 4:3 image is 4% narrower and 8% taller (and consequently 4% more area) than the 3:2 images with the same perspective and AOV. If the aspect ratios, perspective, and AOV are the same for two systems, then the FOVs will also be the same. But if the aspect ratios are different, then to get the same FOV we must frame wider and crop to the desired FOV. Most digital cameras use an aspect ratio of either 3:2 or 4:3. For the same perspective and AOV, a 4:3 image will be slightly more narrow and slightly taller in framing than the 3:2 image. To get the same framing with a sensor that has a different aspect ratio, it is necessary to frame wider and crop. In terms of the FM (focal multiplier), this means that instead of using the ratio of the sensor diagonals to compute the FM, we would instead use the ratio of the sensor heights (the short dimension of the sensor) if we are cropping to the more square format, and the ratio of the sensor lengths (the longer dimension of the sensor) if we are cropping to the more elongated aspect ratio. For example, the dimensions of the Nikon D700 sensor are 36mm x 24mm which gives a diagonal of 43.3mm, and the dimensions of the Olympus E30 sensor are 17.3mm x 13.0mm which gives a diagonal of 21.6mm. This means that the FM for the same AOV between the two cameras is 43.3mm / 21.6mm = 2.00. However, if we frame and crop the D700 image to the 4:3 aspect ratio of the E30, we get a FM of 24mm / 13.0mm = 1.85. On the other hand, if we frame and crop the E3 image to the 3:2 aspect ratio of the D700, we get a FM of 36mm / 17.3mm = 2.08. However, the FMs for the cropped images are less than 1/3 of a stop from an image with the same AOV, so it is a minor point. Sometimes, it may also be of interest to crop the image with the larger pixel count to the same number of pixels and aspect ratio of the image with the smaller pixel count to determine the max EFL that can be achieved with the same detail with the sensor that has the larger pixel count. To do this, we multiply the FL of the system with the larger pixel count by the ratio of the diagonals (in pixels) of its pic with the diagonal of the image with the smaller pixel count. For example, the Canon 5D produces a 4368 x 2912 (3:2 aspect ratio) pixel image which has a diagonal of 5250 pixels. The Olympus E3 produces a 3648 x 2912 (4:3 aspect ratio) image with a diagonal of 4560 pixels. The ratio of these diagonals is 5250 / 4560 = 1.15. Hence, the Canon 5D can squeeze an extra 15% more "digital zoom" by cropping while still maintaining the same pixel count and aspect ratio as the E3, and thus reducing the FM for FOV by the same amount, from 2 to 1.73. However, it is important to note that unless the lenses for the system that is using "digital zoom" can resolve the pixels equally as well as the uncropped image from the system with less pixels, this may result in reducing the IQ of the resulting crop. To get the same FOV / AOV for the same perspective with cameras that have the same aspect ratio, you multiply the FL of the smaller sensor camera by the FM. For example, 30mm on 1.6x gives the same FOV as 50mm on 35mm FF, since 30mm x 1.6 = 50mm. For cameras with different aspect ratios, you simply multiply by the appropriate FM (discussed above) and crop. For example, to get the same FOV as 7mm on an Olympus E30 using a Nikon D700, we would use 7mm x 1.85 = 13mm and then crop the image to 4:3. One side effect of cropping 3:2 images to 4:3 is that it greatly mitigates any softness that might show in the extreme corners. However, we must also realize that this comes at the expense of removing 1/9 of the pixels from the image. But as 3:2 systems generally have more pixels than 4:3 systems of the same generation, this can be done without any detail penalty when comparing systems. Realistically, however, the extreme corners make up so little of the image, and are so close between systems anyway at the same DOF that it is only a consideration for the most hardcore of "pixel-peepers". Please see this image as an example of what would be called a "huge" difference in the corners of different systems at the same DOF. I simply see it as a non-issue, especially considering that the differences elsewhere in the frame matter more by far, but others see it as a serious disadvantage. In any event, framing slightly wider and cropping to 4:3 will basically eliminate even that extreme case. Listed below are tables of common
FMs in relation to 35mm FF for images
using the same AOV. When given in stops, the FM is rounded to the
nearest 1/3 stop. The reason that 35mm FF (24mm x 36mm) is chosen
as a standard is due to its popularity in the days of film and the fact
that there are more lenses made for this particular format which many of
the smaller sensor DSLRs also use. Due to different aspect ratios,
when cropping to the dimensions of the more square sensor, we use the
ratio of the shorter dimensions of the sensor to compute the FM, and when
cropping to the dimensions of the more elongated sensor, we use the ratio
of the longer sensor dimensions. In the case of 3:2 being cropped to
4:3, or vice-versa, this will result in less than a 1/3 stop difference. Compacts:
Rather than relate to an arbitrary standard, such as 35mm FF, the FM between any two systems using the lengths of their respective sensors, or, more simply, either divide the FMs of the respective systems, or subtract their FMs when using stops, using the values in the table above. For example, the FM between a Canon 40D and Olympus E3 can be computed (for the same AOV) as 2.00 / 1.62 ~ 1.23 (2/3 of a stop to the nearest 1/3 stop, or, more simply: 2 stops - 1 1/3 stops = 2/3 of a stop). Thus, 25mm f/2 ISO 100 on 4/3 would have the same AOV, DOF, and shutter speed as 31mm f/ 2.5 ISO 160 on 1.6x, since 25mm x 1.23 ~ 31mm, f/2 x 1.23 ~ f/2.5, and ISO 100 x 1.23² ~ ISO 160 (or, alternatively, f/2 + 2/3 stops = f/2.5 and ISO 100 + 2/3 stops = ISO 160). *There is some confusion as to whether the 4/3 sensors are
13.0mm x 17.3mm or 13.5mm x 18.0mm, since different sources quote
different sizes. This is because Olympus has quoted both sizes, for
whatever reason. This essay uses the 13.0mm x 17.3mm figure since
this is the current sensor size quoted on the Olympus website. Regardless, the practical
differences are so small as to be completely insignificant: a 13.5mm
x 18.0mm sensor would have an FM of 1.92 instead of 2.00 for the same AOV
(which would still round to 2 stops to the nearest 1/3 stop). DOF / APERTURE Before discussing DOF, it is critical to distinguish between "aperture" and "f-ratio". These two terms are used interchangeably but are very different quantities. The aperture is the apparent diameter of the opening in a lens when looking through the front element, and can be calculated as the quotient of the focal length and the f-ratio. For example, the aperture at 80mm f/8 is 80mm / 8 = 10mm. The reason for making the distinction between the two terms is that the aperture is not only intimately related to the DOF, but is also, along with shutter speed, responsible for the total amount of light that reaches the sensor (which is important in terms of noise). The DOF (depth of field) is how much depth from the focal plane of the image is considered to be in critical focus. It is a subjective measure, to be sure, but is not arbitrary. The subjective nature of DOF is accommodated in the DOF formula(s) with the CoC (circle of confusion). The diameter of the CoC is a function of display size, viewing distance, visual acuity, and magnification (the ratio of the final display dimensions to the dimensions of the recording media -- sensor). Because the CoC is a function of the magnification, this means that if we keep all other parameters equal (display size, viewing distance, and visual acuity), it will scale linearly between formats in the same way that focal length scales for the same perspective and AOV, and in the same way that f-ratio scales for the same aperture. For example, if one system had a sensor with twice twice the diagonal as another, we would use double the focal length for the same perspective and AOV, double the f-ratio for the same aperture, and double the CoC for the same display size, viewing distance, and visual acuity. So, while the actual value for the DOF in a particular photo is subjective, whether or not two photos have the same DOF is objective, and can be determined both visually and mathematically. It is important to note that the DOF depends neither on the number of pixels that make up the image nor the sharpness of the lens. This misconception comes from the fact that more pixels and/or sharper lenses usually resolve more detail. However, the resolved detail is independent of the DOF. A simple way to visualize the difference between DOF and resolved detail is to apply a Gaussian Blur to an image. While the blurred image will have less detail, the depth from the focal point that is considered to be in focus will be unaffected. So, while DOF, sharpness, and detail are all intertwined, they are independent quantities. A good way to understand this is to imagine an image taken of the same scene from the same position with the same framing and aperture using cameras with very different pixel counts. Now resample both images to the same dimensions so that they just fit on your computer monitor. The DOFs will be the same. It would be no different when printing the images, so long as they were printed with the same dimensions. So, just as detail cannot be changed with sharpening, DOF cannot be changed with more detail. This brings up the utility of DOF calculators. First of all, all DOF calculators I know of are based on the same AOV rather than the same framing, and the same diagonal display size rather than the same display dimensions. This is only an issue, however, when comparing formats that have very different aspect ratios. Aside from this exception, DOF calculators can be simply used for the relative comparison of different formats, but care must be taken when interpreting their results in terms of the actual DOF. The reason is that most, if not all, DOF calculators use a CoC that is based on a print size of 8x10 inches and viewed with 20-20 vision from a distance of ten inches. So, for larger prints, closer viewing distances, and/or greater visual acuity, a smaller CoC than what DOF calculators default to needs to be used, which is especially true for those who judge DOF on the basis of 100% crops on a computer monitor. Thus, while the CoC, and thus the DOF, still scales by a factor of the focal multiplier between formats, the actual value of the CoC is dependent on other critical factors, such as display size, viewing distance, and visual acuity. We can now make the following generalizations about the DOF
of images on different formats for non-macro situations (when the subject distance is "large" compared to
the focal length),
1) For the same perspective, framing, f-ratio, and display size, larger sensor systems will yield a more shallow DOF than smaller sensors. 2) For the same perspective, framing, aperture, and display size, all systems have the same DOF. 3) For the same focal length, framing, aperture (same focal length and aperture also means same f-ratio), and display size, all systems have the same DOF (but different perspectives). 4) For the same perspective and focal length, larger sensor systems will have a wider framing. If the same f-ratio is used, then both systems will also have the same aperture. As a result, if the image from the larger sensor system is displayed at a larger size in proportion to the sensor sizes, or the image from the larger sensor system is cropped to the same framing as the image from the smaller sensor system and displayed at the same size, then the two images will have the same DOF. Let's demonstrate the DOF equivalence mathematically. As stated earlier, the DOF is the distance from the focal plane where objects in this zone are considered to be critically sharp. However, the distance from the focal plane is not always an even split. When the subject distance is "large" compared to the focal length of the lens (non-macro distances), the far limit of critical focus (Df) , near limit of critical focus (Dn), and DOF can be computed as:
where d is the distance to the subject and H is the hyperfocal distance. We can now compute the DOF behind the subject and the DOF in front of the subject:
Another interesting scenario to consider is that when the subject-camera distance, d, is small compared to the hyperfocal distance, H, then, for the same format, the DOF will be essentially the same for the same framing and f-ratio. For example, 50mm at 10 ft has the same framing as 100mm at 20 ft on 35mm FF. If we shoot the scene at f/2 in each case, we will get the same DOF since the hyperfocal distance is 137 ft for a CoC of 0.03mm (the value used in most DOF calculators for 35mm FF, which corresponds to an 8x10 inch print viewed from a distance of 10 inches), which is much larger than the subject distance of 10 ft. However, were we instead to compare 24mm f/2 at 30 ft to 48mm f/2 at 60 ft (same framing), we would get a different DOF since the hyperfocal distance works out to 30 ft (for a CoC of 0.03mm), which is the same, rather than much larger, than the subject-camera distance. In any case, we can see that the DOF is a function only of the hyperfocal distance (H) and the subject distance (d). The role of the focal length (FL), f-ratio (f), and CoC (c) are contained in the hyperfocal distance: H ~ FL² / (f·c) If we scale the focal length, f-ratio, and CoC by the focal multiplier (FM), the hyperfocal distance remains the same: H' ~ (FL·FM)² / [(f·FM) · (c·FM)] = [FL²·FM²] / [(f·c) · FM²] = FL² / (f·c) = H Consequently the DOF is invariant for the same perspective, framing, and aperture. By expressing H in terms of aperture (a), angle of view (AOV), and the proportion of the sensor diagonal that the CoC covers (p), we get a format independent expression for the hyperfocal distance, and consequently DOF: H ~ a / [2·p·tan (AOV/2)] Thus, for non-macro situations, the DOF for the same perspective, framing, and output size is also the same. A consequence of a larger sensor means that a longer focal length is required for the same perspective and framing, as well as a larger f-ratio to obtain the same aperture. For example, let's consider images taken of the same scene from the same position with the same framing: 1) 5D at 80mm, f/8 (aperture = 80mm / 8 = 10mm) Since the perspective, framing, and apertures are all the same, then for the same display size and viewing distance, their DOFs will also be the same. As a side, if the shutter speeds are also the same (which will require a higher ISO for the higher f-ratios to maintain the same apparent exposure), then the images will be made with the same total amount of light as well, which will result in the same noise if the sensors have the same efficiency. Another reason that DOF is so important, even if DOF, per se, is not an issue to the photographer, is that it is also intimately connected with sharpness, diffraction softening, and vignetting. The reason that DOF affects sharpness is twofold. First of all, as shown above, the DOF is directly related to the aperture, and the larger the aperture, the greater the aberrations, and, in some instances, the greater the field curvature. Secondly, a more shallow DOF means that less of the scene will be within the DOF, and, by definition, elements of the scene outside the DOF will not be sharp. This second point is especially important, since, as noted earlier, DOF calculators usually base their calculations off a CoC for an 8x10 print viewed from 10 inches away. Since so many now evaluate the sharpness of the lens on the basis of 100% crops on a computer monitor, the DOF that is seen at 100% on the computer screen is significantly more narrow than the DOF computed by the calculators. In addition to DOF and sharpness, the aperture is also intimately connected to diffraction. Diffraction softening is the result of the wave nature of light representing point sources as disks (known as Airy Disks). The diameter of the disk depends only on the aperture -- the smaller the aperture, the larger the disk. So long as the diameter of the disk does not exceed that of the pixel (or, in the case of a Bayer sensor with an AA filter, a diameter of two pixels), we will not notice any diffraction softening. The effects of diffraction softening on images can be summed up as follows: For the same aperture and output size, the sensor with the greater pixel count will resolve at least as much detail as the sensor with the smaller pixel count, given that the glass used has the same relative sharpness on the systems being compared. However, for sensors of the same efficiency, the larger sensor system will render less noise and more greater DR, so long as it can remain at base ISO. While it is true that smaller pixels suffer diffraction softening at wider apertures, this is often misinterpreted as meaning that smaller pixels result in softer images than larger pixels at smaller apertures. A good way to understand why this is not the case is via a theoretical example. Consider a two sensors of the same size, one with 2x2 pixels and the other with 1x1 pixels. While the sensor with 1x1 pixels will record double the detail as a sensor with 2x2 pixels, it will also begin to suffer the effects of diffraction softening at twice the aperture (half the f-ratio). For example, let's say that the sensor with the 2x2 pixels begins to suffer diffraction softening at f/8. Then then sensor with the 1x1 pixels will begin to suffer diffraction softening at f/4. Thus, at f/4, the sensor with the 1x1 pixels will render double the detail as the sensor with the 2x2 pixels (lens permitting, and assuming the entire subject is within the DOF). As we approach f/8, this detail advantage will lessen until, at f/8, the detail rendered by both sensors will be nearly the same. The reason the differences are "nearly the same" rather than "exactly the same" is because the distribution of light on the Airy Disk is not uniform, and oversampling will still enable the smaller pixels to render more detail. Hence, the system with more pixels will still resolve more detail at any aperture, it's just that the differences will eventually be small enough as to be inconsequential. In terms of Equivalence, we can think of diffraction softening in the following manner: equivalent images are at the same DOF and output size, which means they will use the same aperture and be displayed at the same dimensions. Since the diameter of the Airy Disk depends only on aperture, and we are displaying the images at the same dimensions, the Airy Disk will cover the same proportion of the image regardless of the sensor size and pixel count. Thus, the image with the greater native pixel count will always render at least as much detail (and usually more) than the image with the smaller native pixel count, assuming, of course, that the lenses used have equal sharpness relative to their respective sensor sizes (see here for more discussion on lens sharpness relative to sensor size). Let us now consider the Canon 20D (1.6x) and Canon 5DII (35mm FF) since they have the same size pixels. If we assume that an image from the 20D begins to suffer from diffraction softening at f/5.6, then the 5DII will be able to render at least the same amount of detail, at the image level, at f/9, since f/9 on FF has the same aperture for a given perspective and framing as f/5.6 on 1.6x (f/5.6 x 1.6 = f/9). Thus, viewed at the same display size, the 5DII image would have at least as much detail as the 20D image. However, to maximize the detail of its 21 MP sensor, the 5DII would begin to suffer diffraction softening at f/5.6 just as the 20D, since its pixels are the same size, but would render appreciably more detail, assuming the subject is within the DOF at f/5.6. So, when maximizing detail, we must account for pixel size, the amount of the subject within the DOF, and the balance of lens aberrations vs diffraction softening in selecting the optimum f-ratio for maximum detail. Regardless, DOF considerations will usually, but not always, be more a consideration than diffraction for images that we want sharp from corner to corner, unless the entire scene is within the DOF. In any event, the effects of diffraction softening will never give the sensor with the smaller pixel count a detail advantage, regardless of sensor size. To get a DOF larger than what the lens can stop down to achieve, we simply frame wider and crop to the desired framing. While the cropping costs us pixels, since the lenses for all systems can stop down to the diffraction limited resolution of the sensor, the detail lost by cropping would have been lost from diffraction softening regardless. For example, an image at 100mm f/32 will have the same DOF and nearly the same detail as an image at 50mm f/16 taken from the same distance and then cropped to the same framing, despite having 1/4 the number of pixels on the subject. This is because the f/32 image has already lost almost the same amount of detail due to diffraction softening, although it will still retain slightly more detail, due to the oversampling of a greater number of diffraction limited pixels still renders slightly more detail than a fewer number of larger pixels. Of course, it would be nice if we didn't have to stop down to increase sharpness for the portions of the image within the DOF, especially as this helps us avoid the effects of diffraction softening. For example, let's say we are taking a pic of a landscape where the entire scene is within the DOF, even at f/2.8. Thus, there would be no reason to shoot at a different f-ratio on different systems to maintain the same DOF. However, the aberrations for larger apertures are more problematical than the aberrations for smaller apertures, and, once again, we realize that larger sensor system will require a higher f-ratio to maintain the same aperture. Thus, even though the DOF may not an issue per se, the aberrations, as well as vignetting, most certainly can be. Of course, one might ask why we simply don't choose the settings on each system that produce the "best" results for each. Well, of course that is how we would use the systems. The section on partial equivalence talks more about this. Putting it all together in terms of AOV, DOF, and shutter speed, let's look at some examples of equivalent settings from common cameras (using the same AOV) with all f-ratios and ISOs rounded to the nearest 1/3 stop, which show how the available DOFs on different formats differ:
SHUTTER SPEED Shutter speed, obviously, is the length of time the shutter remains open to achieve the desired exposure. For a given scene, the total amount of light that makes up the image is a function of the shutter speed and the aperture. In addition, it's important to consider shutter speed when photographing moving subjects and/or to account for camera shake. However, there are times when we do not need to use the same shutter speed since there is enough light to achieve the desired DOF and still have a fast enough shutter. Under these circumstances, the larger sensor system can deliver both deliver more detail (if it has more pixels and lenses capable of sufficiently resolving the pixels) and a cleaner image. For example, let's say we are shooting a landscape. The following settings would be likely candidates for a particular scene:
5D at 24mm, f/11, 1/100, ISO 100 While landscapes are a common scenario, and such a comparison is of practical value to most photographers, we must take care to note that this partially equivalent scenario is only valid when the shutter speeds are sufficiently high to avoid motion blur, and, if a tripod is not being used, to avoid camera shake. If, instead, we were engaged in street photography near dusk, we would need to compare with fully equivalent settings since a sufficient shutter speed would be crucial to stopping motion blur for the required DOF:
So if we are using anything other than base ISO, then we cannot
discount the importance of shutter speed in comparing systems, since the
only time we would not be at base ISO is when shutter speed is a
factor. Under these circumstances, the only way for the
larger formats to enjoy a noise advantage is by using a more shallow DOF, rather
than raising the ISO, to maintain the required shutter speed.
DISPLAY DIMENSIONS The display dimensions is the physical size of the viewed image, whether it be a print or on a computer monitor People, including reviewers, tend to compare IQ at the pixel level, rather than the image level, which leads to incorrect conclusions about the image, unless the images are made from the same number of pixels. If two images are made from a different number of pixels, if we are to compare them at the pixel level, then we need to properly resample the images to a common number of pixels. We can increase the IQ of an image by increasing either the native pixel count or increasing the quality of the individual pixel. Thus, if we compare two images with unequal pixel counts at the pixel level (often referred to as a "100% comparison"), we are disregarding the increase in IQ that comes from the additional pixels, which is discussed in more detail in the Megapixels: Quality vs Quantity section of the essay. For example, let's say we wish to compare the Canon 1DsIII (21 MP) and the Nikon D3 (12 MP). Comparing images from the two systems at the pixel level is the same as comparing 16x24 inch prints from the 1DsIII to 12x18 inch prints from the D3, which is hardly a fair comparison. The best way to compare images is to compare in the manner that they will be displayed. For example, if you are going to print the images, then print them and compare. Of course, this is impractical to do unless we already had access to both systems. And, even if the reviewer provides us with the files to print ourselves, that is a bit of a pain, and certainly not a basis for an objective conclusion that we can share with others as all will not be using the same printer. So, what to do? The easiest solution is to resample both images to a common dimension that is at least as large as the larger image and then compare at the pixel level. The reason to compare at a dimension at least as large as the larger image is because downsampling the larger image will cause it to lose detail, which, I presume, is one of the qualities of IQ being measured in the comparison. In addition, if we are comparing noise, it only makes sense to do so at the same level of detail, so we would apply NR to the more detailed image to match the level of detail of the less detailed image. Of course, care need be taken in the resampling process, since a poor resampling method can lead to incorrect conclusion about the comparative IQ between systems. This is especially true with noise comparisons. We simply cannot downsample the larger file to the dimensions of the smaller file. We first need to apply NR (or a specific form of blur) and then downsample. In any event, it is better to upsample the smaller image rather than downsample the larger image. Again, using the example of the 1DsIII vs D3 comparison, we could resample both images to 54 MP (300 PPI for a 20x30 inch print) and then compare at the pixel level. Of course, there's nothing magical about 54 MP, but we would like to incorporate some kind of "future-proofing" for comparisons with future cameras, and need some value larger than 21 MP, so 300 PPI for a 20x30 inch print sounds like a good "standard", as very few would print larger than this, no matter what pixel counts the future holds or what format they shoot. Of course, for those that do print larger, they would, of course, want to compare at the larger output size. Another option would be for a reviewer to print the images at a variety of sizes (e.g. 4x6, 8x12, 12x18, 16x24, and 20x30 inches) on a top-of-the-line printer, scan the prints, and then compare the scans from the same size prints. 'Tis a pain, but probably the most fair way to compare, although I honestly don't know if it would produce different results than resampling the two images to the "appropriate" PPI for each print size. And, of course, we cannot discount the effects of viewing images on non-calibrated monitors (I've seen more than one comparison where someone claimed the highlights of the image to be blown with several others chiming in that they need to calibrate their monitor). Thus, comparing images that have different pixel counts at the pixel level is a very poor way to compare the IQ between systems. However, the closer the pixel counts are, the better such a comparison will approximate the actual differences. For example, it's reasonable to say that a comparison between the 12.1 MP Nikon D700, 12.1 MP Nikon D3, 12.3 MP Nikon D300, and the 12.7 MP Canon 5D would be easily "close enough" without resampling. But when comparing the 10.1 MP Canon 40D, 10.1 MP 1DIII, or the 10.1 MP Olympus E3 to the aforementioned cameras at the pixel level, we are beginning to stretch a bit (12% difference in linear pixel count), and we are certainly stretching when comparing the 1DsIII to any of the above cameras at the pixel level for native image sizes (32% difference in linear pixel count between the 1DsIII and the D3, for example). So, while no comparison is without its potential problems, the easiest mistake to correct is to carefully resample images to a common dimension, as well as applying NR as necessary for noise comparisons, before comparing at the pixel level.
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IMAGE QUALITY The primary attributes of a camera, in no particular order, are: 1) IQ (Image Quality) But what, exactly, is IQ? That is difficult to define -- so much so
that the term seems to lose any meaning in an objective sense. However,
as will be discussed later in this section, the subjective nature of overall
IQ comes from how we value individual objective components of
IQ. The first step in defining "IQ" is to make the distinction
between "image quality" and a "quality image". This distinction, in
turn, requires us to differentiate between "eye candy" and
"meaningful" photos. The easiest way to distinguish
between these two classes of images is that "eye candy"
requires high IQ to be successful, whereas "meaningful" photos
are successful regardless of the IQ. Typical examples of "eye
candy" would be sunsets, posed portraits, and macro. Examples
of "meaningful" photos are harder to nail down, since most
photos would be "better" with "higher" IQ. Nonetheless,
it is important to acknowledge that there is a class of photography where
image quality, as opposed to a quality image, is all but irrelevant. The fantastic images here hopefully
present a few examples of this class of photography. Sometimes photography is all about technical perfection, such as studio
portraits or product photos for advertisements. Other times, we have photos that are "interesting",
"noteworthy", "moving", etc. These are the types
of photos that have "impact" and can be either "eye
candy" or "meaningful". While IQ can most
certainly play an important role in the success of these photos, the highest IQ camera in the world cannot
find and create such images. It is the photographer who must find
and recognize the significance of a scene, determine how to capture it,
and then successfully do so. Clearly, some images are great because
of what they capture, not how they are captured. Other images are
great not because of what they capture, but because of how they are
captured. So, it is important to keep the concept of IQ in proper
perspective. Since
this essay is concerned entirely with IQ, I feel it's important not to
forget that IQ is only one facet of photography. For some
photographers, it might be the most important aspect of photography.
For others, it may simply be an added plus. But it is time well
spent to reflect on just how important IQ is our own photography, given
that IQ is, at best, merely a means to achieving a quality image, and, at
worst, completely irrelevant to the image. That said, attributes of IQ include, but are not limited to:
detail, sharpness, contrast, color, noise, vignetting, bokeh, and
distortion.
Attributes of IQ do not include subject, composition, focus accuracy, DOF,
etc. These are all attributes of system operation, available lenses,
artistic design, and/or photographer skill. In my personal opinion,
the IQ of all modern DSLRs is exceptional. By far the most important
aspect of a camera to achieving high IQ images, again, in my opinion, is
fast and accurate focus (although I am fully aware that this is
unimportant to many, such as landscape photographers). It's important to realize just how subjective the elements of IQ are. For example, let's
take vignetting, which is considered by many a drawback that distracts from
an image. However, some people even add vignetting artificially
in PP (post-processing) to "enhance" an image. Another
hotly debated element of IQ is noise. While low noise is almost
universally hailed as high IQ, once again, noise is sometimes added to an
image as an artistic effect. More than that, it is not merely the
quantity of noise, but the quality of the noise, that is
important. Simply because one image is more noisy than another per
some mathematical measure does not mean that it has the more pleasing
appearance, even given that low noise is desired. Thus, rather than say that the IQ of
one system is "higher" than another, which only has any meaning
if everyone is on the same page as to what constitutes "higher",
it's better to be far more specific. That is, we should instead say
that A is sharper than B, or B has smoother bokeh than A, or A is less
noisy than B for the same level of detail, or B has less distortion than
A, etc. In other words, we simply cannot assign point values to
each criterion and get an average score, as not all criteria will be given the
same weight by all people, and even feel exactly the opposite on some point
(color, for example). For the most part, the individual components of IQ are objective.
The subjective nature of IQ comes from how we value the various objective
measures of IQ. For example, few people would dispute that sharper
means "higher" IQ or that one image with "better"
bokeh than another would have "higher" IQ. However, let's
say we have two images, one slightly sharper but with a less pleasing
bokeh, and the other less sharp but with a more pleasing bokeh.
Which image has the "higher" IQ? How we value these
different objective elements of IQ is where the subjective comes in. That said, let's discuss the elements of the equipment that affect IQ. In no particular order, they are: 1) The lens (sharpness, contrast, distortion, bokeh, etc.) The reason the size of the sensor matters is that the it greatly
determines the design of the lens that will be used on it. For
example, a sensor that has double the dimensions as another needs glass
only half as sharp and with half the f-ratio to match the sharpness, DOF,
and light gathering ability of an equivalent lens on the
smaller sensor system for images at the same output size and level of
detail. Depending on the image, various elements of IQ will have varying levels
of importance. For example, noise will usually play little role in
ISO 100 images, edge sharpness will play basically no role in shallow DOF
images, sharpness will play little role in images where motion blur is
used for artistic effect, etc., etc. So, while we can discuss the differences
in IQ between systems, we cannot say which elements of IQ are more
important than others. Thus, while one system may have significantly
more appeal on the basis of IQ to a vast majority, that does not mean that
it will have higher IQ in the eyes of all. Hence, when comparing
systems, as mentioned further above, it is best not to compare on the
basis of IQ, but on the basis of specific elements of IQ. So, is it simply a waste of time to compare IQ between systems? Some believe
so, but I disagree. Some elements of IQ that most people value are predictable and
quantifiable on the basis of the sensor and available lenses. This
essay discusses the relationship between the glass and the sensor in how
they determine some aspects of IQ, in particular, detail, sharpness, contrast,
vignetting, and noise. However, it is also important to note the
aspects of IQ that this essay does not discuss, such as bokeh, color, and
distortion. All these qualifiers and disclaimers said, a critical consideration to IQ is the individual's QT (quality threshold),
that is, the point at which additional IQ makes no difference to the viewer at
a given output size. For example, System A may satisfy one person's QT at
8x12, but fail to do so at 12x18. Or, one system may fail to satisfy a
viewer's QT at any output size due to factors that are independent of the image
dimensions (bokeh, for example).
Regardless, it's still not possible to
reach universal agreement that one image, or system, has higher
IQ than another. The reason for this is that images from two
different systems are never identical, and whatever differences there are
between them may appeal to different people differently, as people value
different aspects of IQ differently. For example, let's say one image is sharper everywhere
than another, except in the extreme corners. Which image has the
higher IQ? Different people will have different answers depending
both on the type of photography they do or enjoy, and on the degree to which
the differences in sharpness vary in the images. Another difficulty is
when one system shows higher IQ in one circumstance, but lower IQ in
another. Likewise, a sensor with a weaker AA
filter will render a sharper image, but be more subject to moiré, so in some
instances it will have higher IQ and in other instances lower IQ,
depending on the scene. In other words, there's still a great deal
of subjectivity even within this very narrow set of
parameters for IQ.
Noise is perhaps the most hotly contested of the IQ parameters. As
mentioned earlier, it is not
simply the total amount of noise, but the quality of the noise --
the distribution of the noise in the
various color channels, the balance of color vs luminosity noise, and the
grain of the noise (which is a function of the native pixel count of the
sensor).
Another critical factor that needs to be
mentioned is in-camera processing and PP (post-processing). For
example, comparing images from different systems based on in-camera jpgs
tests the in-camera jpg engine (firmware) as much, if not more than, as it
does the camera hardware. For people who loathe PP, comparing
systems on the basis of in-camera jpgs, of course, makes the most sense.
But such a comparison will have less to do with the IQ potential of a
system and more to do with operational convenience. However, for
people looking to get the most out of their hardware, the "appropriate"
format is RAW. To this end, it is important that we choose a RAW
conversion that portrays each system at its best. Unfortunately, we
are right back to the subjective with what looks "best". In addition, the IQ
differential, while present, may not always be noticeable. Let me
explain that odd statement, since it would seem obvious that if you can't
see a difference in IQ, then there is no difference in IQ. Well, yes
and no. True, if for a particular image you cannot see a difference,
then there is no meaningful difference in IQ. But depending
on how much processing is applied to the image, we may find that one image
withstands that processing much better than the other. In addition,
as mentioned earlier, the IQ differential may not show at one print size,
but become apparent at another. Thus, the
"hidden" IQ of an image may become apparent only under strong PP
or larger prints. It's for that exact reason that so many shoot RAW instead of
jpg. In many cases, the IQ differential between jpg and RAW
conversions are completely insignificant, whereas in some cases, the
differences are substantial. So just as RAW has higher IQ
than jpg, one system may have higher IQ than another, but that higher IQ does not always manifest itself.
Hence, while for one person the IQ difference is non-existent, for another,
the IQ difference is significant. Furthermore, it is fair to say that the elements of
IQ that can be corrected with PP matter less than the elements of IQ that
are resistant to PP. For example, vignetting and distortion are easy
corrections in post (and, in fact, can be automatically
"corrected" in some RAW converters, along with even PF), whereas
detail and DR are not. Other attributes are intermediary -- noise
can be lowered, but this comes at the expense of detail. Sharpness
can be enhanced, but this comes at the expense of artifacts. Still
other effects are primary: bokeh, flare, and moire are often beyond the
abilities of PP (unless one wishes to painstakingly hand-edit every
portion of the image), but these attributes occur in only certain types of
photos, and thus may not be important considerations to some people.
Nonetheless, despite the fact that there is no way around the subjective
elements of IQ and the narrow definition used in this essay, generalizations
about the IQ of different systems can be made. Lastly, I would like to more thoroughly address the issue of output
size, which is a critical consideration in determining what level of IQ,
especially in terms of sharpness and detail, really matters. For
many, if not most, the web is their primary venue for displaying
images. Thus, even a 1.3 MP image is good for a 1280x1024
presentation. However, for those that print their images, 300 PPI (pixels per inch -- not to be confused
with DPI, dots per inch, which is a function of the printer) is considered
about as good as a person will see even with their nose right up against
the image. It's certainly well beyond the QT of the "average" viewer, and 150 PPI is
considered "quite decent". Of course, it depends on your
needs and standards -- "decent" to one person is
"garbage" to another. And, since I bring up printing, it's no small point that the printer
and paper used for the final image is a critical component of the
final image. However, this topic of this essay is comparing camera
systems (camera and available lenses), and it is presumed that we are
taking care to process the images as best we can and use the same quality
printer and paper for both systems. To that end,
let's consider the PPIs for common print sizes (in inches). The table gives the PPIs
for 10, 20, 30, and 40 MP images for the with a native 3:2 aspect ratio / 4:3 aspect
ratio cropped to the given print dimensions:
It's worth noting that since Bayer arrays record only one color per pixel, the PPIs in the above table may be more accurately represented by pixel counts twice as large as given. That is, to truly achieve 323 PPI for an 8x12 print, we may need 20 MP, not 10 MP. However, that is a debate outside the scope of this essay. Anyway, as we can see, the aspect ratio really doesn't affect the image PPI by any significant amount. More importantly, the table above serves to demonstrate how important it is to keep our IQ "needs" in context with the size we print and the expected viewing distance. Basically, what we see is that if 10 MP is "good enough" for up to 13x19 inch prints, then 20 MP of equal quality pixels will be "good enough" for up to 18x24 inch prints, but would offer no meaningful advantage for 13x19 inch prints. But we must pay special attention to the qualifier -- "equal quality pixels". We wouldn't expect 10 MP from a compact to deliver the same quality as 10 MP from a DSLR, for example, nor can we simply upsample a 10 MP image to 20 MP and expect a marked improvement (in fact, the utility of upsampling for the purposes of increasing print quality is of debatable value). Note also how doubling the pixel count doesn't make that much of a difference in the print size, either, and that for print sizes of 8x12 or smaller, 10 MP is already past the point where we can distinguish any differences for equal quality pixels. That said, the reality is that for deep DOF pics at base ISO and smaller print sizes (8x12 inches and smaller, and even larger, depending on the scene and QT of the viewer), few will be able to distinguish, or care, about the differences in IQ between most formats. An interesting article on that point is Michael Reichmann's "You've Got to be Kidding -- No, I'm Not". In any event, there are many elements to IQ that matter even at smaller print sizes, such as bokeh and DR. Thus, even though one system may be able to output a sharper and more detailed image at larger dimensions, these qualities may not be as important as the other qualities of IQ, depending on the image. Of course, the artistic considerations almost always outweigh the technical considerations of an image, which brings us back to the distinction between a quality image and image quality. So what IQ advantages does a larger sensor have? Typically, the larger sensor system will deliver "higher overall IQ" over smaller sensor systems of the same generation in the following ways: 1) Larger sensor systems have less noise and more dynamic
range at any given ISO This, of course, invites the question as to when smaller sensor systems will have "higher IQ". This can happen when: 1) The lenses designed for the smaller sensor system can resolve more
pixels than the lenses for the larger sensor If we think about all these situations, it's easy to see how the balance of these advantages and disadvantages play into the type of photography a person does. The more narrow the scope of photography, the easier it is for one system to be superior to another for the particular application. The more broad the scope, the more difficult it is for a single system to be able to be a clear winner overall. Typically, for cameras of the same generation, the larger sensor is usually at least as efficient as the smaller sensor, since it is featured in the company's "top-end" cameras. However, much of the glass being used on larger sensors is of an older design and outperformed by the newer generation glass. On the other hand, from images I've seen (and linked in the evidence section of this essay), for equivalent images, even much of the older 35mm FF glass delivers sharper images everywhere except the extreme corners with some UWAs, although, as noted, there is more to IQ than just sharpness. As for focus accuracy, unfortunately, I don't know of any "reliable" reports that compare the accuracy and speed of different systems. But in-camera IS is a very powerful plus for smaller sensor cameras, since it is not yet available on 35mm FF cameras to date, with the exception of the Sony A900. While many argue that in-lens IS is superior to in-camera IS (but neither are as good as using a chicken -- click here for a demonstration), it is definitely not superior if the lenses you use do not have it. Regardless of what IQ differences there may be between systems, we have to decide when, if ever, these differences in IQ have any meaning. For example, a Suzuki GSXR-1000 may significantly outperform a Yamaha R-6 on a track, presuming the driver is skilled enough to make use of the extra performance. But if all you use the bikes for is traveling back and forth to work or school, the difference in performance between the bikes is meaningless -- it is more a matter of comfort, gas mileage, and other aspects of the bike that matter more by far. Thus, it is my opinion that for the sizes that most people print
(or display on the web), the differences in IQ
between modern systems are insignificant for the vast majority, just as
the performance differences in bullet bikes is insignificant for most
riders. Instead, the the primary consideration for most people when choosing a system
is not the merely the IQ of the images it produces, but the the types of
images the system can produce and the operation of the system.
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MYTHS AND COMMON MISUNDERSTANDINGS
The motivation behind this essay on "equivalence" was prompted by the many myths about the differences between formats. In particular, the following myths and misunderstandings are common: This is perhaps the single most misunderstood concept when comparing formats. Saying "f/2 = f/2 = f/2" is like saying "50mm = 50mm = 50mm" -- true, but meaningless out of context. In the same way that the same focal length will result in a radically different AOV on different formats, the same f-ratio will result in a radically different aperture for the same AOV. For example, the aperture at 50mm f/2 is 50mm / 2 = 25mm, which has twice the diameter and four times the area as the aperture at 25mm f/2. The central role that aperture plays in photography cannot be understated. For a given perspective, framing, and image display size, aperture determines the DOF of an image, and is also largely responsible for the sharpness of the lens and the effects of diffraction softening. Furthermore, when combined with the shutter speed, it is the aperture, and not the f-ratio, that determines the total amount of light that falls on the sensor. This is a fundamental point that bears repeating: for a given scene and shutter speed, it is the aperture, not the f-ratio, that determines the total amount of light that falls on the sensor. The f-ratio determines the brightness of the light, not the total amount of light. This distinction is critical because it is the total amount of light, and not the brightness of the light, that is the primary factor in image noise: 1) the total amount of light
that falls on the sensor Many believe that the reason larger sensor systems have less noise is because they have more efficient sensors, but this is simply not the case. Larger sensor systems have less noise because the lenses for larger sensor systems usually have larger apertures for a given AOV, and can thus put more total light on the sensor. The only role the size of the sensor itself plays in collecting more total light is that the sensor size determines the focal length for a given AOV, which leads to larger apertures for most existing lenses, and the larger sensor can absorb more total light before becoming saturated. There is, of course, variation in the efficiency of sensors, but this is a matter of generation, not size. Furthermore, whatever differences in efficiency that exist usually have a minor effect on image noise compared to the total amount of light that falls on the sensor. Another common misconception is that since the same f-ratio results in the same exposure, that the total light that makes up an image is unimportant. In fact, it is quite the other way around -- it is the exposure that is irrelevant in terms of the IQ of the final image. This is a difficult concept for many to adjust to. To help explain this, let's consider images taken of the same scene from the same position with the same AOV, aperture, and shutter speed: 1) 5D at 80mm, f/8 (aperture = 80mm / 8 = 10mm), 1/200, ISO 400 Since the apertures and shutter speeds are the same, the images created with the different formats will be made
with the same total amount of light, have the same DOF, and also have the
same noise if the sensors have the same efficiency, despite the
differences in ISOs. The only role ISO plays is to produce the
correct apparent exposure. As a
consequence, for the same efficiency of sensor, the only way for one
system to enjoy a noise advantage over another is by being able to use a
longer shutter speed (being mindful of camera shake and/or motion blur) or
a larger aperture (with a concomitant more shallow DOF). 2) Larger sensor systems are bulky and heavy While larger sensor systems usually are more bulky and
heavy than smaller sensor systems, this is not necessarily the case. In fact, sometimes even the
exact opposite is true. The reason is not as much due to the larger
sensor as it is due to the fact that the lenses designed for
larger sensor systems usually have larger maximum apertures than lenses designed for
smaller sensors. But when
equivalents do exist in both systems, such as the 35-100 / 2 on 4/3 and
70-200 / 4L IS on 35mm FF, the lenses for the larger sensor systems are
usually lighter (but often longer for the telephoto lenses) and less
expensive. There are exceptions, of course, such as the Canon 300 /
2.8L IS on 1.6x vs the Canon 500 / 4L IS on FF. But if reach is the
primary consideration, and light gathering ability secondary, then smaller
sensor systems will usually have a size/weight/price advantage, the most
extreme example of this being the 12x zooms of compact digicams. Thus, smaller sensor systems are usually significantly smaller,
lighter, and less expensive when compared only for the same AOV, but not
when compared for the same AOV and aperture. 3) Images created with larger sensors have a DOF that is "too shallow" and suffer diffraction softening at deeper DOFs Larger sensor systems have the option of a more shallow DOF than smaller sensor systems with available glass, but their DOF can still exceed the diffraction limit. In fact, as a general rule, the smaller the sensor size of a system, the closer its lenses come to the diffraction limit wide open. For the same f-ratio, larger sensors do have a more shallow DOF, but one need only stop down to get a deeper DOF. Even in a limited light situation where the shutter speed needs to be maintained and the larger sensor system will have to up its ISO accordingly, the noise will be the same for the same level of detail if the sensors of the two systems have the same efficiency. Furthermore, larger sensors do not suffer the same diffraction
softening at
the same f-ratio as smaller sensors; the effects of diffraction softening
scale in the same way as the FL scales for the same AOV and the f-ratio
scales for the same DOF, regardless of pixel size. For example,
For example, if 4/3 begins to suffer diffraction softening at f/8 and can
deliver a maximum of 10 MP of detail at f/8, then 1.6x will be able to
deliver at least 10 MP of detail at f/10, and 35mm FF will deliver at
least 10 MP of detail at f/16 . However, diffraction softening may
prevent the larger sensor system from utilizing the full potential of all
its pixels. That is, while 35mm FF can deliver at least 10 MP worth
of detail at the same diffraction limited DOF, the 1DsIII, for example,
will not be able to deliver 21 MP of detail at f/16. But, at the
same DOF, larger sensor systems will never deliver less detail than
smaller sensor systems, so long as they have at least the same number of
pixels. See here for more discussion on
this point. 4) Larger sensors require sharper glass In fact, the exact opposite is true. First of all, as discussed in Myth #1, it is important to compare systems at the same DOF when discussing sharpness, since if we don't, the system with the more shallow DOF will have less of the scene within the DOF, and thus appear less sharp. So, given that we are comparing systems at the same DOF, consider the following analogy: we have two targets, each with the same number of squares on them covering the entire area. If both targets have the same number of squares, then the squares on the larger target will be larger than the squares on the smaller target. Thus, when trying to hit the squares on the smaller target, we need to be more accurate than when throwing at the squares on the larger target. For example, if the larger target has twice the length and width of the smaller target, then we need to be twice as accurate to hit the smaller squares on the smaller target. In the same way, a lens on a larger sensor does not need to be as sharp as a lens on smaller sensor to resolve the same amount of detail. Thus, we could say that two lenses that are able to resolve the same number of pixels on their respective formats have the same "relative sharpness". For example, let's consider a 4/3 DSLR with 10 MP and a FF DSLR with 10 MP. The glass on the 4/3 DSLR will have to be twice as sharp as glass on the FF DSLR to match the performance of the FF DSLR since it's pixels would be half the size. Let's further say that the glass on the 4/3 DSLR is just sharp enough to resolve all of its 10 MP. Then glass half as sharp on the FF DSLR would be able to resolve the same amount of detail, as long as it had at least 10 MP, but would not resolve more detail even if the sensor had more pixels (although the additional pixels would not degrade IQ, either -- this is a false impression caused by examining images at the pixel level rather than the image level). However, if the FF DSLR had glass just as sharp as the 4/3 glass, it would be able to resolve 40 MP -- four times the detail. With lenses that were 70% as sharp as the 4/3 lenses, the FF DSLR could resolve 20 MP -- double the detail. However, we can also imagine the reverse situation. For example, if the 4/3 glass were more than twice as sharp as the FF glass, the smaller sensor would be able to resolve more detail than the larger sensor system if it had enough pixels. Thus, the level of detail in an image depends both on how many pixels the sensor has, and how well the glass is able to resolve those pixels. This is also why FF glass will almost always perform better on FF sensors than on cropped sensors, unless the glass is already so sharp that it can resolve the pixels of the smaller sensor system and the pixel counts are nearly equal, or if the lens for the larger sensor system has particularly poor corner performance, such as the Nikon 70-200 / 2.8 VR, which is discussed in Myth 5 below. Thus, while smaller sensor systems usually have sharper glass, that does not necessarily give them sharper end results -- they need that extra sharpness just to "break even". In practice, however, for the same AOV and DOF, the comparable glass for smaller sensors does not appear to hit that break-even point until the edges of the image, where, in some cases (usually UWA), they outperform FF glass in the extreme corners. But since the larger sensor systems almost always have more pixels and resolve more detail in the central area of the image, if the extreme corners are not satisfactory, you have the option to frame wider and crop. What is meant by "comparable glass"? This is tricky, but generally lenses at, or near, the same price-point. For example, we wouldn't call the Olympus 14-35 / 2 on 4/3 ($1840) or the Nikon 17-55 / 2.8 ($1130) on 1.5x "comparable" to the Canon 24-85 / 3.5-4.5 on FF ($310), since the prices are so different, even though they have nearly the same AOV and aperture range. But we could call them comparable to the Canon 24-70 / 2.8L ($1255) even though the Olympus lens still costs significantly more and both have smaller apertures, since we are now comparing the best against the best from each manufacturer that have comparable AOV ranges on their respective systems. Alternatively, we could also call the Canon 24-105 / 4L IS ($1060) "comparable" since it is also "top glass" for Canon FF, has the same aperture, and a zoom range that includes the AOVs of the aforementioned competitors' lenses. When comparing systems, then, we must
carefully articulate the reasons for choosing the lenses used in the
comparison, since those reasons may be "invalid" depending on the use of
the lens as it is rare to find two lenses from two different systems that
enjoy the same range of AOV, aperture, and price. 5) Larger sensor systems have softer edges and more vignetting than smaller sensor systems Once again, as discussed in Myth #1, this belief is a result of people comparing systems at the same f-ratio rather than the same aperture. At the same f-ratio, the larger sensor system will have a larger aperture, and thus a more shallow DOF, which will result in the areas of the scene outside the DOF being OOF (out-of-focus), as well as greater vignetting. A more fair comparison for edge sharpness is to compare at the same DOF, or, often even more appropriate, at the lenses' sharpest settings, since it is rare that edge sharpness plays a role in high ISO photography. However, it is disingenuous to compare edge sharpness and vignetting by artificially handicapping the larger sensor system with the same f-ratio as the smaller sensor system. Of course, as we know, glass does not have the same sharpness across the image. For example, the issue of telecentricity for UWAs causes a sharp drop in the MTF for many UWAs in 35mm FF lenses (the Nikon 14-24 / 2.8 being a remarkable exception). Thus, the image may be "sharp enough" in the center, but too soft in the corners. This is what happens when comparing, for example, 4/3 lenses with 35mm FF lenses. The 4/3 lenses are sharper than the 35mm lenses (on average), but they need to be sharper to hit the smaller pixels of their sensors. And while 35mm FF glass is easily "sharp enough" for the center of the image, it is sometimes not "sharp enough" for the extreme corners (for some UWAs) even at the same DOF, despite the larger pixels. Thus, near the edges, the sharper glass on a smaller sensor may outperform the less sharp glass on a larger sensor, but the amount of the corners where this reversal in sharpness occurs is dependent on which lenses are being compared, and must be taken on a lens by lens basis. In fact, sometimes the larger sensor system will have the sharper corners (the evidence section of this essay gives examples). An interesting case is the Nikon 70-200 / 2.8 VR which, according to a test conducted by DPR, performs significantly better in the corners on 1.5x than it does on FF even for the same perspective, FOV, and DOF (although, again, the rest of the image is sharper on FF). However, the reviewer noted that this is almost certainly since the lens was optimized for 1.5x, since Nikon had no FF DSLRs, or even plans for one, at the time of the introduction of the lens, and is quite different from how Canon's 70-200 / 2.8L IS performs. Another good example is the Canon 24 / 1.4L II on 1.6x vs the Canon 35 / 1.4L on FF. The two have nearly identical performance at the same DOF in all areas that www.slrgear.com tests. Of course, the 24 / 1.4L II is a newer lens and costs significantly more than the 35 / 1.4L, but such a comparison is fair to make since they are both top level lenses with the same FOV for their respective systems. The question, then, is how would the 24 / 1.4L II on a 50D compare to a 35 / 1.4L on a 5D II? The answer is that the 5DII image would likely deliver more detail, since it has more (and larger) pixels, as well as deliver an optional more shallow DOF, if desired. However, back to the UWA situation, there is another angle to this story. DSLRs with a 3:2 aspect ratio must shoot wider and then crop to match the FOV of a 4:3 aspect ratio, and this cropping all but eliminates the soft corners, if they even exist. For example, for a Canon 5D to match the perspective, framing, and DOF of an Olympus E3 shooting at 7mm f/4, it would have to shoot at 12.5mm f/7.1 and crop to a 4:3 aspect ratio. This would leave 10 MP on the 5D image, which would still match the pixel count and framing of the E3 image, while eliminating the extreme corners. Likewise, the Canon 5DII (FF) has more pixels than the Canon 50D (1.6x), which also gives it more cropping latitude. However, a 50D has more pixels than a 5D, so the 5D would have no such luxury, except if the lens were unable to sufficiently resolve the smaller pixels of the 50D. In this case, a cropped image from the 5D, despite having less pixels, would likely retain the same, or even more detail, in the instances that we would need to frame wider and crop the corners out. Stopping the larger system's lens down to normalize the DOF has the additional benefit of increasing the sharpness of the lens (especially in the corners) and reducing vignetting. Many 4/3 proponents like to cite their glass as being "sharp wide open" with no significant vignetting. However, "wide open" for 4/3 is "stopped down" for 35mm FF. For example, let's compare the Leica 25 / 1.4 on 4/3 with the Canon 50 / 1.4 on 35mm FF. With both lenses at f/1.4, the 4/3 lens will surely have the superior image in terms of sharpness and vignetting, but the 4/3 image with have a DOF that is be two stops deeper. Stopping the Canon lens down to the same DOF (f/2.8) will produce a sharper image (even in the corners) with the same or even less vignetting. If the 35mm FF system must also raise the ISO two stops to match the shutter speed, all this means is that the 35mm FF system loses its noise advantage, but it is not at a disadvantage for noise (for sensors with the same efficiency and images with the same level of detail). Of course, depending on the lenses that are being
paired, sometimes the 35mm FF lenses will be softer in the extreme corners
even for the same DOF, or show ever so slightly more vignetting.
Nonetheless, there is no reason to compare corners and vignetting at
different DOFs, and it is because people compare at the same f-ratio
rather than the same DOF, that this myth exists. 6) Assuming "equivalent" means "equal" It is important to distinguish between "equivalent" and "equal" -- "equal" is a much stronger condition than "equivalent". As stated in the Definition of Equivalence, equivalent images are images that share the following five attributes: 1) Same Perspective If the images were "equal", then they would have to contain the same amount of detail, have the same amount of noise, the same dynamic range, the same color, etc., etc., etc. These elements of IQ are what make "equal" a much stronger condition than "equivalent". There is one way to get images that are "equal", however
-- if the larger sensor system had the same
pixel density as the smaller sensor system, and we could use the same lens
on both systems, then we could get equal images from both systems using
the same settings (focal length, f-ratio, shutter speed, and ISO) and
cropping the larger sensor image to the framing of the smaller sensor
image. While using the same lens and settings on the larger sensor
system sometimes makes sense for macro and long telephoto, it is a
rather odd way to use a camera in any other application. 7) Assuming "equivalence" is based on equal noise "Equivalence" is based on the five
principles listed above and in the definition, which do not include
noise. However, given sensors with the same efficiency, equal noise
will be a consequence of equivalence for images with the same
output size and detail; but, once again, equal noise is not a principle
of equivalence. Likewise, "equivalence" is not based on
equal detail or sharpness, either. The system that resolves the larger number
of pixels will render the most detail, provided the glass is sharp enough
to make use of the extra pixels. Furthermore, the system with more
pixels will render the noise more finely, which will likely give a more
pleasing appearance of noise, so long as the total quantity of noise is
not significantly different. 8) Larger sensor systems have less noise because they have larger pixels Larger sensor systems have less noise than smaller sensor systems because the have the ability to collect more total light, not because they have larger pixels. As the beginning of the Noise section of the essay states, the quantity of noise in an image is determined by the following three factors: 1) the total amount of light that falls on the sensor For a given sensor size, smaller pixels will collect less
light per pixel, but there will be proportionally more pixels, so
the total amount of light collected will be the same. Thus, while
having more pixels does add more noise into the image than fewer pixels,
it also adds in more detail. By properly downsizing the image to a
smaller pixel count, or applying NR (noise reduction), this increase in
detail can be traded for lower noise, thus taking us back to the fact that
it is because larger sensor systems can gather a greater total amount of
light, rather than the size of the individual pixels, that is the reason
that larger sensor systems have less noise. 9) Comparing images at 100% rather than the same display dimensions It is common for people to compare images at 100% -- that is, to compare images at the pixel level. However, such a comparison would only make sense if each image was made from the same number of pixels. For example, it makes no sense to compare a 4x6 print with an 8x12 print, just as it makes no sense to compare, for example, a 2000 x 3000 pixel image with a 4000 x 6000 image. To properly compare image, we need to compare at the same display dimensions, that is, at the same print size and/or the same number of pixels. Some argue that the process of resampling the image with the smaller
pixel count to the dimensions of the image with the larger pixel count is
unfair to the smaller image since the upsampling introduces a new variable
into the comparison. However, this variable is always introduced
regardless. That is, we either resize an image for web display, or
the printer will automatically interpolate the image for printing,
regardless of whether we upsample or not. The most fair method for
comparing at 100% is to carefully resample both images to a common dimension, so that neither system is favored. Usually, we would
choose a dimension at least as large as the larger image, since
downsampling the larger image reduces detail. 10) Larger sensor systems gather more light and have less noise than smaller sensor systems For the same AOV, lenses for larger sensor systems often have larger apertures which gather more light than smaller sensor systems, and thus deliver less noisy images even if the sensor for the larger sensor system is less efficient (to a degree). However, choosing a larger aperture also results in a more shallow DOF, more vignetting, and softer corners. For fully equivalent images, all formats gather the same total amount of light and thus have the same total noise (for equally efficient sensors) and DOF. On the other hand, in some circumstances for systems that have in-camera IS or IS lenses may be able to gather more light and have either a noise advantage over other systems lacking IS by being able to use a slower shutter speed which can be a significant advantage for non-tripod and non-flash photography where motion blur is not a factor, or even desirable.
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EXPOSURE, APPARENT EXPOSURE, AND TOTAL LIGHT
It is important to define exposure, apparent exposure, and their relationship to total light. These three terms are best described mathematically: 1) Exposure = Intensity x Time where intensity is defined in photons per unit time per unit area that fall on the sensor. This means that exposure represents the density of the light falling on the sensor -- photons per unit area -- which is inversely proportional to the square of the f-ratio and directly proportional to the duration of the exposure. For example, were one to double the f-ratio, the intensity of the light would one fourth as much, as would the exposure, and halving the shutter speed would double the duration of the exposure, which in turn would double the amount of exposure. Note that the exposure, Intensity x Time, is a component in both apparent exposure and total light. Of the three quantities, the apparent exposure is what is usually meant when people say "exposure" (just as people often say "aperture" to mean "f-ratio"), whereas the total light is the most important measure in terms of IQ, since the total light that makes up an image is the dominant factor in image noise. The total amount of light that falls on the sensor is determined by the following four factors: 1) The brightness of the scene Let's discuss why the same f-ratio results in the same exposure for the same scene and framing, regardless of the focal length. The amount of light that passes through a given area in a given time is inversely proportional to the square of the distance from the source. For example, if we are twice as far away, then 1/4 as much light would fall on the same area in the same time. To maintain the same framing for a given sensor size, we would use twice the focal length if we were twice the distance from the scene. This means that for a given f-ratio, the aperture would be twice the diameter, since the aperture is the quotient for the focal length and f-ratio. If the aperture has twice the diameter, then it will have four times the area, since the area is proportional to the square of the diameter. So, while the light passing through the aperture onto the sensor is 1/4 as bright twice as far away, for the same f-ratio the aperture has four times the area. Thus, the same amount of light will fall on the sensor. Next, let's consider the case of two sensors, one with twice the dimensions of the other, capturing an image of the same scene with the same framing from the same position at the same shutter speed. The smaller sensor will use half the focal length of the larger sensor, which means its aperture will be half the diameter, and thus 1/4 the area, for the same f-ratio. This means that it will collect 1/4 as much light. However, the sensor is 1/4 the area. Thus, 1/4 as much light is falling on a surface with 1/4 as much area, and thus the exposures are, once again, the same. It is often more convenient to calculate the values of exposure, apparent exposure, and total light in stops (ev's). The definition of 0 ev is the amount of light from a "properly exposed" image at f/1 and with a shutter speed of 1 second. However, were we to halve the shutter speed to 1/2 second keeping everything else the same, we would have an exposure made with half the light, so we would expect the ev to be one stop lower. However, the ev for f/1 and 1/2 second is 1 -- a stop higher, not a stop lower. This is because ev's are units for "properly exposed" scenes, so it is assumed that if we are using half the shutter speed, then, for a properly exposed image, the scene would be twice as bright, not the amount of light reaching the sensor, hence the ev will be one stop higher. On the other hand, if we exposed a scene at f/1 with a shutter speed of 1/2 second, the exposure will be one stop lower than a pic of the same scene at f/1 and a shutter speed of 1 second. So, while we can compute both the exposure and apparent exposure in ev's by taking the base 1/2 logarithms of the formulas above, we need to modify this simple transformation a bit when calculating the total light in ev's to account for the amount of light reaching the sensor, rather than the amount of light of the metered scene. For convenience, just as focal lengths are often expressed in terms of 35mm FF equivalents, the ev for total light will also be normalized in terms of the area of a 35mm FF sensor (864mm²): 1) Exposure (ev's) = log1/2 [Intensity x Time] For example, let's consider an image captured at f/4, 1/250, ISO 400: A) Exposure = log1/2 [(1/4²) x
(1/250)] = 12 ev Light is composed of photons, and the total light is simply the total number of photons that land on the sensor. In contrast, the "exposure" is the average number of photons per unit area. So two different formats cannot simultaneously have the same exposure and same total amount of light since the same amount of light is being distributed on different areas. However, if we use the same perspective and focal length, and then crop the larger sensor image to the same FOV as the smaller sensor image, then we will have the same exposure and total light (as well as the same DOF) if we use the same f-ratio. However, in practice, the only time I know of when an image from a larger format uses the same perspective and focal length, and is subsequently cropped to the same framing as the smaller format, is when the larger format is focal length limited, or for greater apparent magnification (macro). For a given scene, perspective, framing, and shutter speed, the total amount of light that falls on the sensor will be a function of the aperture, which is the apparent diameter of the opening in the lens as by looking through the front element. It can be calculated by taking the quotient of the focal length and f-ratio. For example, the aperture for 50mm f/2.8 will have a diameter of 50mm / 2.8 ~ 18mm. Clearly, the larger the aperture, the more light that passes through the lens and onto the sensor for a given scene and shutter speed. Since the area of the aperture is proportional to the square of its diameter, doubling the aperture diameter will quadruple the area, and thus quadruple the total amount of light that passes through the lens onto the sensor for a given scene and shutter speed. The total amount of light is determined solely by the shutter speed (often indirectly controlled by ISO) and the f-ratio. The problem with using the f-ratio to regulate the total amount of light is that it also affects DOF, sharpness (particularly in the corners), and vignetting. The problem with using the shutter speed to regulate the total amount of light is that it affects camera shake, if a tripod is not being used, as well as motion blur. Clearly, we want to maximize the total amount of light that makes up an image to minimize the noise, but noise, in my opinion, is rarely as much a factor as other IQ considerations. So where does exposure fit in to all of this? First of all, it's important to note that when most people say "exposure", they usually mean "apparent exposure" -- how bright or dark an image appears. Using these terms interchangeably causes as much confusion when comparing formats just as when "aperture" and "f-ratio" are used interchangeably. For example, if we take an image of the same scene using the same f-ratio at 1/100 ISO 100 or 1/400 ISO 400, we will have the same apparent exposure, that is, the images will appear correctly exposed. But they will not have the same exposure since the ISO 100 image will have been created with four times as much light per unit area. As a side, it's worthwhile to note that an underexposed image pushed to the proper apparent exposure will have more noise than an image that has the proper apparent exposure in camera. For example, an underexposed image at 1/100 ISO 100 pushed two stops will have more noise than an image 1/100 ISO 400. Thus, it's best to properly expose (as in, get the proper "apparent exposure") in-camera rather than in post (see here for examples of this). Let's now put all these concepts together with examples. We'll consider some scenarios using the E3 (4/3), 40D (1.6x), and 5D (35mm FF). The reason I exclude 1.5x sensors from this scenario is that the results are basically identical to 1.6x sensors. Furthermore, it needs to be mentioned that 4/3 uses a different aspect ratio (4:3) than the 40D and 5D (3:2). The consequence of this, in terms of the total amount of light collected, is that a rectangle with a 4:3 aspect ratio has 4% more area than a rectangle with the same diagonal and a 3:2 aspect ratio. This results in a difference of approximately 1/18 of a stop of light -- completely insignificant (any differences less than 1/3 of a stop as regarded as "insignificant" in this essay). Even if we frame wider with the 3:2 systems and crop to the same FOV as 4/3, this still results in a bit less than 1/3 stop loss of light for the 3:2 systems (see here for more on this). So, the differences between the 4:3 and 3:2 aspect ratios will be ignored in the examples below. That said, let's consider images of the same scene from the same position with the same AOV, aperture, and shutter speed from three systems: E3: 40mm, f/4 (aperture = 40mm / 4 = 10mm), 1/500, ISO 100 -->
exposure = 13 ev, apparent exposure = 13 ev, total light = 11 ev The perspectives are the same since both pics are taken from the same position. The AOVs are the same since 40mm x 2 = 50mm x 1.6 = 80mm. In addition, since the apertures and the shutter speeds are also the same, both the DOF and total light that falls on each sensor are the same which means the noise will be the same for the same sensor efficiency. However, while the apparent exposures are the same, note that the exposures are not the same, since the larger sensors use lower f-ratios. Alternatively, we can realize that the exposures are not the same since the same total amount of light is distributed over a larger area making for a lower intensity. OK, let's now consider another scenario, again shot from the same position with the same AOV and shutter speed, but the same f-ratio rather than the same aperture:
E3: 40mm, f/4 (aperture = 40mm / 4 = 10mm), 1/500, ISO 100 -->
exposure = 13 ev, apparent exposure = 13 ev, total light = 11 ev The perspectives are the same. The AOVs are the same. Since the apertures are not the same, the DOFs are not the same (it's increasingly more shallow for the larger sensors, which will also, consequently, have softer edges and more vignetting). In addition, even though the shutter speeds are the same, more total light that falls on the larger sensors because the apertures are different. Thus, for the same sensor efficiency, the larger sensors will have less noise. However, both the apparent exposures and the exposures are the same since the f-ratios and shutter speeds are the same. Using a larger aperture to gather more light, and thus less noise, is a primary method by which larger sensor systems achieve less noise and works well when either the DOF plays less a role in the image than does the noise, or when a more shallow DOF is actually preferred. Now, one last scenario to consider. And again, the
same scene from the same position with the same AOV, but now using the
same aperture and ISO and thus different f-ratios and shutter speeds: The perspectives are the same. The AOVs are the same. The DOFs are the same. The shutter speeds are not the same. The total light that falls on each sensor is not the same (once again, the larger the sensor, the more light it receives). The apparent exposures are the same. The exposures are not the same. On the occasions when using a tripod and motion blur is not an issue, or there is sufficient light that camera shake is also not an issue, you can sacrifice shutter speed to maintain the desired DOF whilst capturing the image with lower noise and/or more DR. Of course, it is important to also recognize that when one system has IS lenses or sensor IS that another system does not, the IS system can also use a lower shutter speed to its advantage to gather more light. Regardless, it's important to note that the exposure itself is not important, per se, in any of these scenarios. It is the "total light" and the "apparent exposure" that actually matter. Thus, it is critical to understand the difference between "total light", "exposure", and "apparent exposure" when comparing systems. In the same way that more pixels give the option of a more detailed image with more noise or a less detailed image with less noise (by using NR and/or downsampling), a larger sensor gives the option of getting less noise by trading shutter speed, DOF, or a combination of both, but that this advantage can be offset, and even reversed, in some instances when the smaller system has IS lenses or sensor IS that the larger sensor system does not. However, these advantages are often overstated since there are situations when these trades cannot be made, and the larger sensor will not have a noise advantage over smaller sensors, or IS will be of limited use due to motion blur of moving subjects. So when we talk about a noise advantage, this advantage is a function of the total light that makes up the image. For the same perspective, AOV, DOF, shutter speed, and apparent exposure, all sensors, regardless of size receive the same total amount of light. Thus, under these conditions, for the same efficiency of sensor, all formats will have the same amount of total image noise (but not necessarily per-pixel noise, unless the images have the same number of pixels). In the end, images are created with light, and it is the total amount of that light, and not the intensity of the light, that is the important measure in terms of IQ. We can think of creating an image as like filling a pool with water. A small sensor with a fast lens is like using a small hose with a lot of pressure. A larger sensor with a slower lens is like using a larger hose with less pressure. Of course, the analogy is not perfect, because it gives the impression that using a large hose with a lot of pressure is the best option. However, the reality is that by using a fast f-ratio on a larger sensor, we also get a more shallow DOF, more vignetting, and softer edges, which is not always the best option. Nonetheless, it is an option, not a requirement, that is available to larger sensor systems. To recap, it is important to understand that equivalent images are based on the same total light and not the same exposure. At first read, this sounds ludicrous, but when we discover that we normally mean "apparent exposure" when we say "exposure", just as people usually mean "f-ratio" when they say "aperture", all falls into place. These distinctions are key, and in combination with same output size, the basis of pretty much all the confusion in understanding equivalence. We now bring the essence of a photograph back to the fundamental point that it is the total amount of light used to create the image, not the intensity of that light, that is central.
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NOISE / DYNAMIC RANGE
When people refer to noise in an image, what they mean is the NSR (Noise-to-Signal Ratio), which is the ratio of the total amount of noise to the total amount of signal. An image with a lot of noise may still not look noisy if the amount of noise is small compared to the amount of signal. This is why the total amount of light is such an important quantity since it represents the total signal. The quantity of noise in an image is determined by the following three factors: 1) the total amount of light
that falls on the sensor Noise has two
components of noise: shot, which is the noise from the light
itself, and read, which is the noise added from the sensor and
supporting software. If two systems collect the same total amount of
light, then they will have the same total amount of shot noise, and the
shot noise is the dominant source of noise in most photos. For a given
scene, framing, and distance from that scene, the total amount of light is
determined solely by the aperture (not the f-ratio) and the shutter speed. So, if one system uses a larger aperture than another,
and the sensor can absorb the additional light without oversaturating, then it will have
less shot noise. This is why larger sensor systems have less overall image
noise than smaller sensor systems -- the lenses for larger sensor systems
usually (but not always) have lenses that have larger max apertures for a
given AOV of the scene and the larger sensors can absorb more light in
proportion to their larger areas. Not coincidentally, this larger max
aperture is
what also allows for a more shallow DOF. This is the reason that formats
larger than 35mm FF do not necessarily have a noise or shallow DOF
advantage over 35mm FF -- the lenses for larger formats don't usually have
larger max apertures for a given perspective and framing. For a given perspective and framing, the total amount of light that falls on the sensor is determined solely by the aperture and the shutter speed. The efficiency by which this light is captured is a function of many variables, primarily the sensor design (e.g. Bayer), the efficiency of the microlens covering, the percentage of the light transmitted by the color filters, and the QE (quantum efficiency) of the sensor. The efficiency of the signal amplification is a function of not only the sensor, but the supporting hardware, such as the ADUs (Analog-to-Digital Units). The quality of the noise can be divided into luminance/color noise and pattern noise / banding, and can often matter significantly more to the IQ of an image than the quantity of noise. Both shot noise and read noise are less distracting than pattern noise and banding because they are completely random. The quantity of shot noise is proportional to the square root of the total amount of light (total signal). Thus, the only way to lessen the NSR from the shot noise is to increase the signal, and the only way to boost the signal is to use a longer shutter speed and/or larger aperture. As discussed earlier in this essay, a longer shutter speed can only be used when neither motion blur nor camera shake are an issue, and a larger aperture also leads to a more shallow DOF, a softer image (particularly in the corners), and more vignetting. In terms of the total signal, the amount of light lost by traveling through the glass of the lens is insignificant, so there is no improvement to be made there. The microlens covering over the sensor, which directs the light that falls on the sensor into the pixels is also near 100% efficiency for modern cameras, so, again, there is no improvement to be made there, either. However, for Bayer sensors, each pixel records only one color (usually 25% red, 25% blue, and 50% green), and thus anywhere from 1-2 stops of light is lost. In addition, the color filters absorb as much as a stop of the light, making the true light loss from 2-3 stops. By contrast, Foveon sensors record three colors for each pixel, so the first source of light loss that plagues the Bayer design, 1-2 stops, is avoided. On the other hand, they still have the same issue of light loss from the color filters (and perhaps even more, since the Foveon design may require a different type of color filter that is less efficient). So, while Foveon sensors, depending on efficiency, may have less luminance noise (and thus be superior for BW images for the same sensor size), due to technical difficulties in separating the colors, they have significantly more color noise than Bayer sensors, and are thus more noisy overall for color images. An elegant solution to regain much of the lost light is to use a prism, rather than filters, to separate the colors, which is used with some video cameras. A major difficulty with this system is that the amount that light bends through the prism is a function of the color of the light. Thus, it is quite a feat to make all the different colors that will be grouped as "red", "green", or "blue" to bend together as a group so that they strike to appropriate pixels, since the prism will not have multiple elements like a lens to correct for this. Of course, the more pixels a sensor has, the smaller the pixels need to be, and the more of an issue this becomes. In addition, the prism solution requires three sensors instead of one, which increases the size, cost, and complexity of the camera, and lends the technology to be more "appropriate" for smaller sensor systems. So while it is entirely possible that smaller sensor systems may achieve similar noise performance to larger sensor systems by using superior technology in the future, which would be too large and/or costly to implement on larger sensor systems initially, it may also be that the noise advantage they offer may come at the expense of smaller pixel counts. Since the two sources of noise (shot and read) are uncorrelated, the total noise is computed as the square root of the sum of their squares. Thus, if we let S represent the total signal (total amount of light), the shot noise will be proportional to sqrt S. Likewise, letting R represent the read noise, we can now compute the combined noise, and the NSR (which is what we usually mean when we say "noise"): Total Noise: N = sqrt (S + R²) For those that are mathematically inclined, we can see by the formula that where there is ample light, and noise matters the least, the shot noise dominates, whereas in areas of low light, where noise is the most distracting, the read noise dominates. The role the pixel size plays in noise is important to discuss, since many feel that more pixels degrade image quality by forcing smaller pixels, and thus more noise. Let's investigate this by considering two equally efficient sensors of the same size, where one has four times the pixel count of the other. Hence, the pixels of the sensor with the larger pixel count will have twice the linear dimensions and four times the area as the sensor with the smaller pixel count. For equally efficient sensors, the read noise of a pixel is the same regardless of its size. Thus, two equally efficient sensors with the same number of pixels would have the same total read noise. But what about sensors with different pixel counts? Consider, for example, two sensors of equal sizes, one with pixels twice the dimensions of the other. Thus, a single 2x2 pixel on one sensor would cover the same area as four 1x1 pixels on the other sensor. Since the total area covered is the same, the shot noise will also be the same, as both situations will collect the same total amount of light. Let's arbitrarily say that the read noise for each of the pixels is 1. How will the noise between the two sensors compare? Since noise sums in quadrature, the total read noise for the four 1x1 pixels would be R = sqrt (1² + 1² + 1² + 1²) = 2, which is double the read noise for the single 2x2 pixel. However, as the total shot noise for the four 1x1 pixels is the same as the single 2x2 pixel, the total noise for the four 1x1 pixels will be less than double that of the single 2x2 pixel. How much less depends on how much the shot noise contributes to the total noise vs the read noise contribution. If the shot noise dominates (ample light), then the sensor with the smaller pixels will deliver up to double the detail (depending on the ability of the lens to resolve the smaller pixels) with roughly the same noise. If read noise dominates (low light, shadows), then the additional detail will come at the expense of double the noise. In the case where the read noise dominates, we can apply NR (noise reduction) to the image with the smaller pixels and regain the noise performance of the larger pixel image by sacrificing the additional detail. Hence, for equally efficient sensors of the same size, more pixels gives the option of more detail (and, depending on the circumstances, more noise), or the same detail with the same noise via the application of NR. An excellent demonstration of this can be seen here. All that said, as mentioned in the beginning paragraph of this section, while we often speak of the noise (NSR) of Camera A vs Camera B, what many overlook is that it is not merely the amount of noise, but the type of noise that is important. It is not only possible, but likely, that one image may be more noisy (higher NSR) than another, yet have a much more pleasing look due to the quality of the noise. For example, color noise is usually much more distracting than luminescence noise. In addition, fine noise is usually considered much more appealing than coarse noise. In other words, a more noisy image with a finer "grain" may well look better than a less noisy image with a clumpier "grain", depending on how close the overall quantities of noise are (an excellent demonstration of this is given here and here). To this end, having more pixels, even at the expense of more noise, can lead to a more appealing overall image, but this is most certainly subjective. Of course, if the more detailed image has the same, or even less, noise than the less detailed image after NR is applied to match the level of detail, then the system with the more detailed, yet more noisy, image will have a substantial IQ advantage by being able to better balance noise and detail in post. Regardless, it is important to consider the types of images where noise is even an issue. This, of course, depends greatly on both the QT (quality threshold) of the viewer which is strongly influenced by print size and the viewer's "noise floor" -- that is, the point at which less noise has no noticeable impact on the IQ of the image. For example, while an ISO 100 image from 35mm FF has less noise than an ISO 100 image from 4/3, the noise advantage of 35mm FF may be unnoticeable to the viewer at ISO 100. Of course, the "noise floor" is likely a function of the print size and viewing distance as well. For example, the noise in an image may not be distracting in a 5x7 print, but become an issue in a 12x18 print. Furthermore, the effects of noise are more noticeable in some scenes than others -- noise is less distracting in areas with lots of detail, but more distracting in areas with less detail. Another important consideration when this noise presents itself in regular patterns rather than random "grain", which is extremely distracting. In addition, we have to consider the balance of noise in the different color channels. One image may be less noisy than another overall, but exhibit significantly more noise in one of the color channels which will give it a less appealing overall look. In other words, while noise is most certainly an important consideration in the IQ of an image, the quantity of the noise most likely is less important than the quality of the noise. Nonetheless, as discussed above, it meaningless to discuss noise without considering the detail of the image. Thus, just as we compare the sharpness of images at the same output size, we compare the noise in images at the same level of detail. It makes no sense to say that one image has less noise than another, when it also has less detail, since NR (noise reduction) can be applied to the more detailed image to get a cleaner image at the expense of detail. Thus, for a fair comparison of noise between images, we would first apply NR to the more detailed image until it matches the level of detail of the less detailed image. Often, it is more an issue of how the noise is processed, rather than the quantity of noise, that is the primary issue. For example, some manufacturers may select a higher black point that gives cleaner shadows, but also destroys all detail. So, we must take care to once again consider noise vs detail. Directly related to noise is DR (dynamic range) -- the range of brightness the camera can capture from darkest to brightest. DR at the pixel level can best be described in a quantitative manner as the ratio of the most intense light a pixel can record to the least intense light a pixel can record and can be calculated thusly: DR = log2 (Full Well Saturation / Noise Floor). For example, if the saturation point of a pixel is 80000 electrons and the noise floor is 20 electrons, then the DR for the pixel is log2 (80000 / 20) ~ 12 stops. As discussed above, the condition of "same efficiency" means that four pixels half the size (equal area) will have the twice the read noise (noise floor). Thus, the DR for four pixels half the size (equal area) on an equally efficient sensor will be log2 (80000 / 40) ~ 11 stops. Once again, as above, with the application of NR, this loss of DR can be regained by sacrificing the additional detail. In addition, it is important to note the "bit depth" of the RAW output (e.g. 14 bits vs 12 bits) plays no role in the DR. However, the bit depth does play a role in how smooth the tonal gradations are from dark to light, and thus, in some circumstances, a greater bit depth may give the illusion of greater DR, and also is more tolerant of radical PP, such as HDR. In addition, it is possible that a greater bit depth also allows for a smoother signal amplification leading to less noise (this is merely a hypothesis and I have no evidence one way or another to support it at this time). For any given ISO and shutter speed, larger sensors enjoy substantial advantages over smaller sensors when it comes to noise and DR since larger sensors will gather more light in these circumstances. However, fully equivalent images are made from the same total amount of light, and thus, given equally efficient sensors, have no noise advantage over smaller sensor systems. But, given that larger sensor systems of the same generation usually have more pixels, they will usually be able to render more detail and smoother tonal gradations. Thus, the noise advantage of larger sensors is limited to situations when it can use a lower shutter speed than the smaller sensor system, such as good light, tripod use where motion blur is not a factor, flash photography when the balance of the light from the flash and the ambient light is not an issue, or when a more shallow DOF is used by trading f-ratio for ISO. And, once again, all these factors only matter if we are talking about sensors that have the same, or nearly the same, efficiency. Regardless, it is likely that it is the quality of the noise, more so than quantity of the noise, that is the primary factor in distinguishing between the IQ of two systems for modern cameras in terms of noise. Just as with any element of IQ, noise is very subjective, and different people will reach different conclusions about which image is more pleasing, even if the numbers clearly point to one image or the other as having more overall noise.
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LENS VS SENSOR
A digital image is made with a lens and a sensor, but which matters more? The simple answer is that neither is more important than the other. The sensor size and efficiency in combination with the lens aperture determine how much light makes up the image for a given shutter speed, which is the primary source of noise in an image. Furthermore, a larger sensor is proportionally more tolerant of lens sharpness. That is, a lens need only be half as sharp on a sensor twice as large to deliver the same detail. This is point is largely overlooked by proponents of smaller sensor systems who claim that the sharper glass makes the smaller sensor systems superior. However, there are other characteristics of IQ that are entirely dependent on the lens, such as bokeh, flare, and distortion, which often matter more than sharpness alone. And then there are other IQ attributes, such as color, vignetting, and PF (purple fringing), which are properties of both the sensor and lens. However, as the latter two elements of IQ are relatively simple fixes in PP (and can even be automatically corrected for either in-camera or with many RAW converters), they are of significantly lesser concern. The reality of existing lenses is that glass for the larger sensor systems almost always allow for a larger aperture, and thus a more shallow DOF, if desired, and less noise. However, the downside is that lenses for larger sensor systems (usually wide-angle) sometimes have a sudden drop-off in their MTF curves at the edges of the image circle, which makes for softer corners, even when compared at the same DOF and same output size. However, as the Nikon 14-24 / 2.8 has shown, this issue may vanish with more modern lens designs, although other modern lenses, such as the Canon 14 / 2.8L II, do not hit full stride in the corners until f/5.6. However, this may be a design compromise necessary to deliver desired bokeh characteristics and low distortion, or it could be a cost-cutting solution with designers feeling that sharp corners are unnecessary at DOFs less than f/5.6 on 35mm FF, or a compromise required to keep the lens small and compact. Whichever the case is, the Nikon lens has shown that sharp corners on 35mm FF UWA is not endemic to the format, but a choice in the design of the lens. What compromises need to be made for these choices, is something only the lens designers know. Nonetheless, we can summarize the advantages of lenses for larger sensor systems as follows:
and the advantages of lenses for smaller sensor systems:
The bottom line is that comparing lenses or sensors independently usually leads to inaccurate perceptions about the images that different systems are able to produce. In terms of the IQ of the final image, it is the specific lens-sensor system that needs to be evaluated, not one or the other.
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MEGAPIXELS: QUALITY VS QUANTITY
In earlier times in digital photography, most of the talk about IQ revolved about megapixels, and it was commonly believed that more were better. When Foveon came out with their sensor, where each "sensel" records three colors as opposed to the one color per sensel of the Bayer sensors, the debate between quality and quantity began. While the debate between Bayer and Foveon is not discussed in this essay, most seem to agree that, in most circumstances, a Foveon sensor performs as well as a Bayer sensor with twice the pixel count in terms of detail rendered (it is much more complicated than this, but, as I said, that discussion is left out of this essay). In recent times, however, as the megapixels of Bayer sensors have continued to rise, there are many who believe that there is a "sweet spot" for the number of megapixels, and exceeding that number actually reduces IQ. This belief arises primarily from the belief that more pixels increases noise and decreases DR (dynamic range) since, for a given sensor size, more pixels means smaller pixels. However, this myth arises from people comparing at 100% rather than at the same level of detail. Since more pixels yield more more detail (the amount of extra detail being dependent on the lens' ability to resolve the additional pixels), this additional detail can be sacrificed via NR (noise reduction) to regain the noise and DR levels of the image of the smaller pixel count. However, even when noisier, it is not unlikely that the finer grain of the noise from an image with more pixels will be more appealing than the clumpier noise in an image made from fewer pixels. So, in fact, more pixels simply give more IQ options than fewer pixels, in terms of detail, noise, and DR. In fact, the debate between how much the quality of the pixel contributes to IQ vs the quantity of pixels is very much analogous to the debate between how much the lens contributes to IQ vs the sensor. One simple example demonstrating pixel quality vs pixel quantity would be to shoot the same scene from the same position with both a Canon 5D (FF) and Canon 40D (1.6x) using the same lens and the same settings (focal length, f-ratio, shutter speed, and ISO). Then crop the 5D image to the same framing as the 40D image, and print (or display) both at the same size. The crop from the 5D image will look identical to the 40D image except it will have less detail, as the crop will have 5 MP as opposed to the 10 MP of the 40D image, but less noise and more DR, since its pixels are larger. However, we can apply NR to the 40D image to sacrifice the detail and match the 5D crop in terms of noise and detail, if we choose. But we cannot sacrifice the noise and DR of the 5D crop to match the detail of the 40D image. Furthermore, the final output size of the image cannot be overlooked as playing a significant role in how many pixels are "enough". For example, as only 8.64 MP are necessary for 300 PPI on an 8x12 print, the differences in IQ between the 40D image and 5D crop may be entirely insignificant at that print size. The advantage of more pixels would only make a difference in larger prints, and even then, only when detail matters more than noise and DR. The relationship between pixel count and detail is further complicated by the ability of a lens to resolve a pixel, which depends not only on the pixel size, but on the lens aperture and how far the pixel is from the center of the image. For example, consider the Canon 50 / 1.4 on a Canon 5D (click the FF tab). At f/1.4, it is somewhat soft in the center and has horrific corners (of course, at f/1.4 the DOF is so shallow that the corners are all but meaningless since few, if any, scenes at f/1.4 would have the corners are within the DOF). By f/2, the center is looking very good, but the corners are still atrocious (although, as above, the DOF at f/2 is still so shallow that this is a non-issue). By f/2.8, the lens is performing admirably across the image circle, and by f/5.6, where the corners could well matter, the lens is all but perfect (in terms of sharpness across the frame). But the 5D has 12.7 MP. What might we expect on the 5DII, which has 21 MP? While www.slrgear.com has not run the test on the 5DII (or 1DsIII, which also has 21 MP), DPR has tested the Canon 50 / 1.4 on the 1DsIII (also 21 MP). The results show that while relatively soft wide open, by f/5.6 the lens can still resolve the smaller pixels all the way to the extreme corners. In other words, the extra pixels of the 5DII may not help much, if at all, at f/1.4, but may show considerable increase in detail by f/5.6. Thus, depending on the lens and the aperture used, the benefits of a greater pixel density can greatly vary. Further complicating the issue is that diffraction softening will begin to take effect earlier on a 5DII compared to a 5D since it has smaller pixels, which will mitigate the advantage of the greater pixel density at the opposite end of the DOF range as well. Lastly, we need to consider camera shake and motion blur. To take advantage of smaller pixels, the shutter speed must be proportionally higher for moving objects, which may require an increase in ISO (thus adding more noise). For stationary subjects, while we may not need to up the ISO for a higher shutter speed for reasons of motion blur, we may need to do so to account for camera shake in many circumstances. So, depending on the lens and aperture used, and where the image needs to be sharp (center vs corners), and the ISO needed to maintain the necessary shutter speed, the IQ advantage of more pixels may vary greatly. Nonetheless, regardless of the lens performance, more pixels will not produce an inferior image at the image level, so long as the sensor is at least as efficient. For example, downsampling the 21 MP 5DII image to the 12.7 MP of the 5D, or the upsampling the 5D image to the dimensions of the 5DII image, any lens will would perform better overall on the 5DII due to the larger pixel count. However, the increase in detail will never be the full 65% improvement that the differences in pixel counts suggests, and will be highly dependent on the both the lens and the aperture used, as well as the circumstances of the shot. This brings us to the consideration of the sensor size. For a given pixel count, a larger sensor will have larger pixels and thus be less demanding on the lens. Smaller sensors, on the other hand, require sharper lenses to resolve the smaller pixels. The question becomes, then, if the lenses for the smaller sensor system are sharper by a great enough margin to overcome this disadvantage. In fact, some might argue that they might be more than sharp enough and even be able to resolve more pixels than the larger sensor system. Well, of course, this depends on the individual lenses being compared. However, from numerous comparisons between lenses on various formats at www.slrgear.com, I have found that at the same AOV and DOF (not the same focal length and f-ratio), that lenses for larger sensor systems usually outperform lenses on smaller sensor systems overall for the same tier of lenses. Lastly, we need to discuss what effect the smaller pixels due to larger pixel counts have on noise. At the pixel level, of course, there will be more noise. In fact, there will even be more noise at the image level for equivalent images. However, there will also be more detail. By applying NR (noise reduction) to the more detailed image to match the detail of the image with the smaller native pixel count, we can regain the noise performance by sacrificing the additional detail. One might ask what the utility of the additional pixels is if NR must be applied to match the noise level and DR of an image made from fewer, but larger, pixels. The answer is simple: depending on the image, detail often matters more than noise -- with the more detailed image we have the option of more detail with less noise, or the same detail with the same noise. The system with the smaller native pixel count never has the option for more detail. In terms of DR, we need to distinguish between pixel DR and image DR, as well as DR and the fineness of the tonal gradations. Let's discuss this via an analogy of two equally efficient sensors: Sensor A has 40 MP and Sensor B has 10 MP. Despite being equally efficient, Sensor A will be more noisy than Sensor B, since it will have more pixels, and thus it will have less DR, but it will also render more detail. However, that detail can be traded for lower noise and more DR with the use of NR. But, perhaps more importantly, Sensor A will have finer tonal gradations which will likely matter more than the DR. Since the sensors are equally efficient, then if a pixel of Sensor A saturates at 20000 photons, then a pixel from Sensor B will saturate at 80000 pixels, since it has four times the area. Let's assume that 60000 photons land on a pixel of Sensor B. In that same area, then, 60000 photons would land on 4 different pixels of Sensor A. Let's say that 10000 photons land on one pixel, 18000 land on another, 19000 on another, and thus 13000 on the last. So, while the pixel from Sensor B is well below its saturation limit of 80000 photons, two of the pixels from Sensor A are blown (oversaturated). However, even with two blown pixels, Sensor A will deliver a smoother tonal gradation, even though it will have less DR. But, with the application of NR, Sensor A will be able to match the noise and NR of Sensor B, while still yielding a smoother tonal gradation. So, are more pixels still better? Yes. But the advantages of more pixels is not as extreme as the difference in pixel counts seems to suggest, unless the lenses are capable of resolving the additional pixels.
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EQUIVALENT LENSES
The definition of an equivalent lens is a lens that produces an equivalent image that another lens produces on another format. In other words, equivalent lenses will have the same aperture (not f-ratio) for the same AOV. For example, the 135 / 2L on 35mm FF is equivalent to an 85 / 1.2L on 1.6x and a 70-200 / 4L (IS) on 35mm FF is equivalent to a 35-100 / 2 on 4/3. Many people very much dislike this terminology and consider it "misleading" and even "dishonest". Typically, they feel that it is sufficient to think in terms of AOV and exposure, and ignore the importance of DOF, as well as the significance of difference between exposure and apparent exposure. To this end, we often hear people saying "f/2 is f/2 is f/2" regardless of format. However, that statement is every bit as misleading as saying "50mm is 50mm is 50mm" regardless of format. Just as 50mm yields different AOVs on different formats, f/2 will result in a different aperture for a given AOV and thus a different DOF as well as admitting a different total amount of light onto the sensor which will result in different noise levels. Recalling one of the top ten misunderstandings of equivalence, that "equivalence" does not mean "equal", we need to realize that equivalent lenses are not identical, of course, and there can be important operational differences between them. For example, while the Canon 135 / 2L on FF is equivalent to the 85 / 1.2L II on 1.6x, the 135 / 2L is much less expensive, larger (but lighter), and focuses much faster. Another example is the Canon 24-105 / 4L IS on 35mm FF. Its closest equivalent on 1.6x is the 17-55 / 2.8 IS (equivalent to a 28-88 / 4.5 IS on 35mm FF). But while the 35mm FF lens has the advantage of more range at both the wide and long end, it suffers the disadvantage of not being able to use the high precision f/2.8 AF sensor as the 17-55 / 2.8 IS on 1.6x can. Nonetheless, while there most certainly may be operational differences in many instances, equivalent lenses produce equivalent images on their respective formats. Of course, we must remember that "equivalent" does not mean "equal", and there may be important IQ considerations to consider between equivalent lenses that are not subject to equivalence, such as bokeh, flare, PF, etc. An important consideration when choosing systems is to compare available lenses in equivalent terms of the same format. Often, lenses may have the same AOV, but not the same maximum aperture. For example, the Canon 50 / 1.4 has the same AOV as the 30 / 1.4 on 1.6x and the 25 / 1.4 on 4/3, but it's max aperture (50mm / 1.4 = 36mm) is larger than either. To match the aperture of the 50 / 1.4 on FF, we would need a 30 / 0.9 on 1.6x and a 25 / 0.7 on 4/3, neither of which exist. On the other hand, smaller formats will often have smaller and lighter lenses when such larger apertures are not needed. For example, the Canon 400 / 5.6L on 1.6x is equivalent to a 640 / 9L on 35mm FF, which does not exist. And even if it did, the AF system would not function at that f-ratio. In fact, 35mm FF does not even currently have a 600 / 5.6L as an option. Thus, FF shooters are "forced" to use a 600 / 4L IS, which is huge and expensive, or crop the images for shorter glass yielding less pixels on the subject, and thus less detail. So while lenses for 35mm FF typically have the advantage for more shallow DOFs (if desired) and more light gathering ability, they lack smaller and lighter lenses with smaller apertures to achieve the same reach as smaller formats. In addition to this drawback, 35mm FF lenses sometimes have the same minimum focusing distance for the same FL, not for the same effective reach. For example, the minimum focusing distance of the 135 / 2L is 0.9m whether on 1.6x or 35mm FF, but 135mm on 1.6x has an EFL (effective focal length) of 216mm on 35mm FF, and the 35mm FF equivalent of the 135 / 2L on 1.6x is the 200 / 2.8L, which has a minimum AF distance of 1.2m. Hence, the smaller sensor system can almost always frame more closely. And then there are some lenses which have no equivalents in either AOV or DOF between systems. For example, the Tokina 10-17 / 3.5-4.5 FE on 1.6x corresponds to a 16-27 / 5.6-7.1 FE on 35mm FF. There is no lens even remotely like that available, and, even if there were, it would not AF on anything less than a Canon 1-series body. Also, the 70-300 / 4-5.6 on 4/3 corresponds to a 140-600/ 8-11 on 35mm FF. If such a lens were made for 35mm FF, and it would AF, I'm sure there are many 35mm FF shooters who would love such a lens. Lastly, there is the notion that some lenses on one system are "superior" to the lenses available on another system. So, while this section has discussed "equivalent lenses" in terms of AOV and DOF, it has not addressed "equivalent lenses" in terms of IQ. First of all, it's important to understand what role the sensor size plays in terms of image sharpness. A sharper lens on a smaller sensor does not necessarily deliver a sharper image (see Myth #4 for more explanation on this point). Of course, this must be taken on a lens by lens basis, and the properties of sharpness, bokeh, distortion, flare resistance, etc., may well be superior for the lens of one system for some elements of IQ, and inferior for other elements of IQ. In addition, we must also take care to compare the lenses as they perform on their respective systems, rather than on their own merits. For example, it makes no sense in terms of the capability of the system to say "Lens A is sharper than Lens B" if it does not produce a sharper image for equivalent settings (same AOV, DOF, and output size) on the format the lens is used on, since the sensor size plays a significant role in how well the lens performs on a given system. Likewise, if we are comparing bokeh or distortion, we have to be careful to compare at the same AOV and DOF, lest me make inaccurate assessments about the lens performance on the system it will be used on. Of course some might argue that the lens lasts longer than the sensor technology, and consider evaluating the lens alone in terms of an "investment" in the system. However, how a lens performs on a system has everything to do with the size of the sensor and not the technology level of the sensor. The technology level of the sensor determines noise performance, not sharpness, bokeh, flare, distortion, etc. In the end, we must consider the available lenses for a system when choosing which system best suits our needs, but we must understand how these lenses perform on the sensor that will be recording the images. To this end, understanding that equivalent lenses produce equivalent images (same AOV and DOF), along with the operational differences between the lenses, is an important consideration when choosing a system.
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IQ VS OPERATION
There are, of course, many other operational advantages to smaller sensor cameras, not the least of which are size, weight, and cost. For example, compacts fit in your pocket and even have video, which give them quite an advantage over DSLRs in that regard. It should not merely be noted, but stressed, that for the sizes that most people print, and the DOFs that most people prefer, IQ is likely the least of their concerns with modern cameras, and operation is the overwhelming difference by which to choose. Among the most critical of the operational differences to consider is the camera's AF system -- IQ means nothing if the pic is OOF (out-of-focus) or a focus lock cannot be achieved. In fact, it's amazing how much attention the megapixel counts and how little the AF system receives, since even a tiny focus error can greatly reduce the detail of an image. A great write-up on the importance of accurate AF is given here at www.slrgear.com. To a lesser degree, but sometimes just as important, if not more so, is shutter lag -- the time lag between when the shutter is depressed and when the capture is taken. For some types of photography, the moment can be lost in that split-second (although, from personal experience, more often than not it is the hesitation from the operator that is usually the dominant factor for missed shots of narrow opportunity). In addition, it must be said that the availability of a feature, such as in-camera IS, will most certainly, under many circumstances, go a long way to creating a higher quality image. Yet in-camera IS is available only on some 1.5x and 4/3 DSLRs as well as compact digicams. FF DSLRs currently rely on in-lens IS which is not available for all, or even most, lenses (Sony's upcoming FF DSLR may change all that). Of course, one can argue that the larger sensor DSLR has better noise performance, but this can only be achieved if there is enough light to sacrifice shutter speed, or if one sacrifices DOF to use the same f-ratio. Furthermore, certain lenses that are specifically designed for the cropped DSLRs may have various IQ advantages (less PF, flare, distortion, etc.). In addition, if the smaller sensor camera has a more efficient sensor, it will have less noise for the same DOF. And, of course, none of these points matter if you don't have the camera with you in the first place. In other words, if the system is too heavy to carry up the mountain, or the weather is wet and the camera is not weather sealed, or the camera is too large to be used discreetly, then it really doesn't matter how good the IQ is if the camera is not going to be used. But we must keep in mind that images created from systems with smaller sensors do not have more DOF, do not have sharper corners (except, in some instances, usually wide angle, in the very extreme corners for the same DOF), do not vignette less, and do not suffer diffraction softening better, than their larger sensor counterparts. These myths are wholly attributable to people comparing systems at the same f-ratio rather than the same DOF. In general, the advantage of larger sensor systems are basically shallow DOF and higher IQ for times when shutter speed may be "safely" lowered to maintain the desired DOF. On the other hand, smaller sensor DSLR systems often have size, weight, operational, and cost advantages that outweigh the DOF and IQ differences between the systems. It is always paramount to compare the systems in terms of IQ, operation, and available lenses/accessories. Each individual must the seek the best balance of these considerations and choose the system that best meets their needs.
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HYPOTHETICAL COMPARISON
The purpose of this section is to demonstrate the principles of equivalence without muddying the water with differences between various systems in terms of operation, available lenses, and unequal pixel counts. Of course, the operation, available lenses, and pixel count are not only important considerations, but many times the primary consideration, in choosing a system. However, by eliminating these variables in this section, it is my intent to more clearly illustrate the relationship between the sensor and the lenses in terms of IQ. We begin with a hypothetical Olympus FF DSLR system, which I will call the "F3", that is simply a scaled version of the current Olympus E3. It will use a 34.6mm x 26mm sensor (twice the length and width of the E3 sensor and same 43.3mm diagonal of 3:2 FF sensors) that has the same pixel count, design, and efficiency of the current sensor in the E3. Since the F3 sensor has twice the dimensions as the E3 sensor and has the same pixel count, the F3 pixels will have have twice the dimensions as the E3 pixels. Thus, the glass for the F3 only needs to be half as sharp as the glass for the E3 to resolve the pixels. In addition, the F3 pixels would have four times the area as the E3 pixels, which means the F3 will have the same noise as the E3 when using an ISO four times higher, as we are assuming the same efficiency of sensor. In addition, since we are using twice the FL on the F3 as the E3 to get the same perspective and FOV, we will also be using four times the ISO and half the f-ratio and to get the same total amount of light, and consequently DOF, for the same shutter speed. Thus, the IQ of the systems will be virtually identical, since they gather the same total amount of light, have the same efficiency of sensor, and the glass for each system is equally sharp relative to the pixel size. Let's now consider the following equivalent systems: E3 (ISO 100-3200) As we can see, the lenses for the F3 system seem almost painfully slow but they will nonetheless produce identical images to the E3 system, since we are assuming that the sensors have the same efficiency and the F-system glass is exactly half as sharp as the E-system glass. The lenses all have the same effective reach, the same apertures (which means they will admit the same total amount of light and produce the same DOF range), and will produce equally sharp images with the same noise for the same DOF and shutter speed. The advantages of the lenses for the F-series system is that they would be often be lighter (the two stops smaller f-ratio affects the weight more than the larger image circle and longer FL) and less expensive (it is much less expensive to make a lens that has double the image circle and is half as sharp). The disadvantage of the F-series lenses is that, despite often weighing less, they would be physically longer, which, while probably not much of an issue below 100mm, may be a substantial minus above 200mm. In addition, it's possible that at least some of the lenses, if not most, for the E-system would likely be able to frame closer for the same AOV, which can often be a big plus. Another operational advantage of the E-system is that it may be able to have a more "generous" spread of AF points. All FF systems have their AF points clustered near the center, and I do not know if this is simply how manufacturers choose to group them, or if the tighter grouping is a necessary consequence of the larger sensor. On the other hand, since the same size AF sensors would cover a smaller relative area of the scene, the F-system would likely have more accurate AF. This brings us to the viewfinder size and brightness. The lenses for the E-system in this equivalent example are twice as bright, but transmit the same total amount of light. Thus, for the same size viewfinder, both the E and F-systems would have the same brightness despite the differences in the lens brightness. But if the F-system has a viewfinder that is proportionally larger (four times the area) than the E-system, then it's viewfinder will necessarily be dimmer. OK. Let's consider the following two high-end systems: Once again, the images created with the two systems would be virtually indistinguishable even given that the F-system lenses are half as sharp. However, the differences in price and weight will be even more extreme than in the previous example, since the E-system lenses are getting much closer to the maximum possible f-ratio of f / 0.5, with the design and cost of such lenses becoming increasingly difficult and expensive. Let's now discuss about the future expandability of the systems. Olympus could make faster F-series lenses that many people would enjoy, and still at moderate size, weight, and cost. For example:
F3 (ISO 400-12800) This would give the F3 an optional more shallow DOF when desired, and the option to trade DOF for a lower ISO to get a cleaner image. On the other hand, for slower lenses that cover a lot of range:
E3 (ISO 100-3200) and
F3 (ISO 400-12800) the size/weight advantage will likely go to the E-system, which will most certainly cost less as well. So we see that the advantages afforded by a larger sensor system have everything to do with the economics and availability of the available glass as well as the number of lenses, their speed, and focal length. The equivalent glass for the larger sensor system will often be physically longer (at least for the longer FLs, since it needs double the focal length for the same perspective and AOV), but be significantly less costly and often lighter for larger aperture glass. The break-even point likely falls around f/5.6 on FF (f/2.8 on 4/3), with cost and weight favoring the F-system for faster glass, and favoring the E-system for slower glass. In addition, we need to consider the likely advantages of closer MFDs for a given reach and a greater spread of AF points. In the end, it's important to reiterate that this is a hypothetical situation to describe the relationship between the glass and the sensor in terms of the IQ of the image. As of now, the choice between systems is not so straightforward, as there are no FF DSLRs that are simply scaled up versions of smaller sensor DSLRs, nor are there lenses specifically designed for each sensor that have perfect equivalents in the other formats. Thus, operation, available glass, and IQ must all be taken together in choosing which system is best for the individual.
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RELATED ARTICLES
The links below are articles related to the discussion in this essay. However, the inclusion of these articles does not necessarily mean that I agree or endorse the entirety of their content (although, for the most part, I do). They are simply additional resources on the same subject. A similar article on different formats Lots of great tutorials (DOF, noise, etc.) More great tutorials (Bob Atkins) Noise and Quantum Efficiency (Clarkvision) Practical Use of DOF and Diffraction More on Sensor Size and Diffraction (plus Diffraction Calculator) More on DOF (plus DOF Calculator) The Importance of Accurate Focus
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CONCLUSION
Photography is all about the image. But before we talk about IQ, we must first get the image. In other words, IQ plays no role in an image that is out of focus. IQ plays no role in an image that is missed due to slow focus or shutter lag. IQ plays no role in an image that was not captured because the equipment was too bulky to be carried to the mountain top or too conspicuous to be used. On the other hand, just as the amazing television series, Planet Earth, is significantly more impressive on a 52 inch HDTV than it is on a 36 inch conventional TV set, the IQ of an image, as well as the optional ability to achieve a more shallow DOF, can greatly enhance the impact that an image has. There are plenty of TV shows and movies where the type of TV set they were viewed on would make no difference whatsoever, but then there are plenty where it would. In other words, sometimes IQ is paramount, and sometimes it is not. Just as we do not all watch the same TV shows, or even have the same opinions about the value of the shows that we do watch, different photographers will not take the same types of photographs or give the various elements of IQ the same value as another. Each photographer must balance the operation of a system against its IQ potential in concert with their own skills to decide what system best gets the job done for the type of photography that they do. The debate between different sensor formats is very much like debate between primes and zooms. While top-quality primes may have higher IQ, allow for a more shallow DOF, and be better suited for low-light photography, they do not zoom. That singular advantage of a zoom trumps all the advantages of a prime for many photographers, and so it is when comparing formats. In other words, rather than being a matter of one format being "better" than the other in terms of IQ, it is more often a matter of available lenses, differences in DOF capabilities, and operational convenience. The bottom line is that we use a camera to create images. It is important to understand the advantages of any particular system as a whole, both in terms of IQ and operation. The purpose of equivalence is to help evaluate the IQ end of that consideration, and, in conjunction with our individual "quality threshold", make an informed choice as to which system, or systems, best meet our personal needs for the photography that we do.
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ACKNOWLEDGMENTS
This essay was possible only because of the immense help and education I have received from others. At the risk of slighting many of those who have helped me by failing to mention them by name (especially those whose images are linked in the Evidence section of this essay), I would like to particularly thank Lee Jay for giving me the bulk of my education as well as providing many of the examples, Amin Sabet for challenging my biases and also contributing many of the examples, and Steen for arguing with me so vigorously over the writing of this work and helping me shape the language and tone. Without the help from many others, this essay would not have been possible, and I am indebted to them for their help and contributions. Also, a special shout-out to "bad doggie", who was one of the most vocal opponents of Equivalence, and with whom I was constantly fighting. The arguments didn't really help me form this essay, but I just loved that guy. He was, by far, the most fun of the "bad guys". I also liked a few of the pics he posted. More a photographer and less a gear-head. So, "bad doggie", if you're reading, take it easy! : ) --joseph james
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