Category Archives: Comparison

Debunking the Myth of Full Frame Superiority (Again)

 

FFvAPSC

Equivalence does not prove the superiority of full frame (FF) over crop sensor (APS-C, M43) cameras. In fact, equivalence shows that equivalent photos are equivalent in terms of angle of view, depth of field, motion blurring, brightness, etc…including QUALITY. Yes, equivalent photos are equivalent in quality.

Refer to the illustration above where we have a full frame lens (BLUE) on a full frame sensor (GREEN). Some full frame sensors are now capable of shooting in crop mode (APS-C) where only the area in RED is used. When a crop sensor LENS is used on a full frame sensor, only the area in RED is illuminated and the rest of the areas in GREEN are in complete darkness and therefore do not contribute to light gathering. This is also true when the full frame is forced to shoot in crop mode with a full frame lens; the camera automatically crops the image to the area in RED and the rest of the areas in GREEN are thrown away.

As per the illustration above, we can see that the central half of the full frame sensor is really just an APS-C sensor. If indeed, a crop sensor is inferior in terms of light gathering then logic will tell us that every center of a full frame shot will be noisier than the rest of the frame. We know this is not true. The light coming in from the lens spreads evenly throughout the entire frame. Total light is spread over total area. As a matter of fact, the central half is the cleanest because lenses are not perfect and become worse as you move away from the center.

Now suppose we have a full frame 50mm lens in front of a full frame sensor. Notice that the crop mode area (RED) does not capture the entire image that is projected by the 50mm lens. The angle of view is narrower than full frame (GREEN). There are several ways we can capture the entire 50mm view while using crop mode:

  1. move backward
  2. use a wider lens (approx 35mm)

Both methods allow the RED area to capture more of the scene. A wider scene means more light is gathered. It means that if we force the RED area (APS-C) to capture exactly the same image as the GREEN area (FF) we will be forced to capture more light! More light means less noise! In equivalent images, APS-C is actually cleaner than full frame!!!

For example, if we go with option #2 using a wider lens, equivalent photos would be something like this:

RED (APS-C): 35mm, 1/125, f/5.6, ISO 100
GREEN (FF): 50mm, 1/125, f/8, ISO 200

This is exactly what the equivalence theory proposes. The difference in f-stop is to ensure that they have the same depth of field given the same distance to subject. The faster f-stop for APS-C (f/5.6) guarantees that TWICE more light is gathered. Notice that the full frame is now forced to shoot at a higher ISO to compensate for the lesser light coming in due to a narrower aperture given by f/8. So if we are to use the same camera for both shots, say, a Nikon D810 to shoot in normal mode with a 50mm lens and in crop mode using a 35mm lens, the crop mode image will be noticeably better. In equivalent photos, crop mode comes out one stop better. In equivalent photos, the smaller sensor results in BETTER quality!!!

The story does not end here though. The full frame shot has twice the area of the crop mode shot. If both images are printed at the same size, the crop mode shot will need to be enlarged more than the full frame shot. Enlargement results in loss of quality and the full frame image will have an advantage over the crop mode image. Whatever the crop mode shot gained by the increase in gathered light is lost by a proportional amount during enlargement. In the end, both full frame and crop mode shots result in exactly THE SAME print quality!!!

Bottomline, full frame will not give you cleaner images than crop sensors, assuming that they are the same sensor technology (e.g. D800, D7000, K5). They will result in equivalent print quality if forced to shoot equivalent images.

Full frame superiority busted!

Debunking Equivalence Part 2

In my previous post Debunking Equivalence I covered in detail the major flaws of this concept called “equivalence”. Mind you, not everything in equivalence is wrong. Equivalence in field of view and depth of field make total sense. What does not make sense is the equivalence in exposure. This “exposure equivalence” is what full frame fanbois sell to unsuspecting gear heads. It is supposed to prove that full frame is superior to APS-C, m43 and smaller sensor cameras. 

In this post, I will use basic math to debunk the myth. Just enough math that I learned when I was in first grade — seriously.

Recall the equivalence comparison between m43 and full frame:

m43: 25mm, f/5.6, 1/125s, ISO 100

FF: 50mm, f/11, 1/125s, ISO 400

Ignore the ISO settings for now. Let us concentrate on the f-stop and shutter speed settings. The reason, they say, that f/5.6@125 is equivalent to f/11@125 is that both gather the same amount of light by virtue of the difference in focal length. The longer 50mm lens will have the same entrance pupil diameter as the 25mm lens. The difference in focal length of course is proportional to the sensor size. 

Now let us use arbitrary units of measure and consider the ratio X/Y, where X is the total amount of light and Y is the sensor size. Supposing that for m43 we have the ratio 4/8, a full frame sensor (4x area), according to equivalence, would have a ratio 4/32. Again:

m43 = 4/8 vs FF = 4/32

So total light is constant at 4 units and the denominators are the respective sensor size units 8 and 32 for m43 and full frame respectively. Still with me? Obviously, they are not the same. Not in any known universe. This is why for the same amount of light, the full frame will come out two stops underexposed. And this is why equivalence fanbois will insist that an increase in ISO is necessary; the full frame shot is very dark! Now we know that bumping the ISO does not increase the amount of light but will make the image brighter. I’m not sure how to represent that in numbers because nothing has changed really in terms of light. ISO bump is fake. It’s a post-capture operation that does not change the exposure or captured light. Furthermore, an ISO bump introduces noise and that is why equivalence forces the comparison to be performed at the same print size. This method of cheating does miracles for the fanbois. Let’s see how it works:

If we agree to compare at the same print size of 16 units, we now have 

m43: 4/8 upsampled to 4/16

FF: 4/32 downsampled to 4/16

Magic!!! They are now the same! They are equivalent! This is true for any print size therefore equivalence is correct!!! Therefore full frame is superior because at the same f-stop it will have gathered more light! 

Well, not so fast! The amount of light did not change. It was constant at 4 units. The apparent changes in signal performance was not due to light but due to resampling. Do not equate resampling to total light. They are not the same and are completely independent of each other. Resampling is like changing your viewing distance. I can make my crappy shot look cleaner simply by viewing it farther away. Did I change total light by moving away from the image? Stupid isn’t it?

That is the very naive reasoning behind equivalence. Not only is the conclusion stupid but the assumption here is that there is absolutely NO NOISE! Noise is ever present. Noise is present and proportional to the incoming light and a property of the sensor itself. Let’s see what happens when we introduce noise. 

Supposing that noise is 1 unit. We now have:

m43: signal = 4/8, noise = 1/8

FF: signal = 4/32, noise = 4/32

Therefore the signal to noise ratio (SNR) are as follows:

m43 = 4:1

FF = 4:4 or 1:1

The full frame is obviously inferior! It makes sense because it was underexposed by two stops (4x)!!! If you boost the signal by increasing the ISO you are boosting noise as well. In low light situations where noise is more pronounced, a 4:2 SNR for m43 will be 4:8 for full frame. There is more noise than signal in the full frame image! At 4:4 SNR for m43, full frame is at 4:32. There is nothing but noise in the full frame. You just can’t underexpose indefinitely and bump the ISO! That doesn’t work in all situations. This is why images at higher ISOs look bad. There is more noise than signal in low light situations. Yet, equivalence fanbois will try to convince you that ISO 6400 on m43 is the same as two stops underexposure plus ISO 25600 in full frame. It’s not. 

So again, the equivalence fanbois could not accept this fact. At the sensor level, equivalence has made the full frame look really bad. What can they do? Cheat again! Force the comparison to use the same print size. At a print size of 16 units, noise will be increased or decreased proportional to how much you upsample or downsample. We have:

m43: signal = 4/16, noise = 2/16

FF: signal = 4/16, noise = 2/16

So now the SNR for both are equal at 4:2! Can you see how they manipulate the numbers? They are using image size (number of pixels) to circumvent noise and stupidly equate this to light gathering. The total amount of light has not changed. How could anyone possibly attribute the changes in SNR due to resampling to light? It does not make any sense at all! Look closely though because this SNR is for the entire image. Most of the signal will be concentrated on the brighter areas. In the darker areas noise will show its teeth. In instances were full frame is severely underexposed (SNR 4:32) there is no saving it. It would look crap. M43, on the other hand will happily chug along with 1:1 SNR or better. 

This is why when you start comparing two full frame cameras with different resolutions you will notice variations in SNR results at different print sizes (Megapixel Hallucinations). If the SNR changes even when the sensor size is held constant then obviously sensor size does not matter. Therefore total light, being proportional to sensor size, by itself does not tell the whole picture. What matters is the RATIO of total light to sensor size, otherwise known as EXPOSURE. For SNR to be the same, exposure must be the same for sensors with the same properties (i.e. sensel pitch, efficiency, etc…). Size does not matter. 

Equivalence debunked…again!

Understanding the Effects of Diffraction

This post is a continuation of the previous article that I wrote about resolution and diffraction. I highly suggest that you read that one first so that you will gain a basic understanding of these concepts.

One thing that a lot of people still fail to understand is the absolute effect of diffraction on image resolution. A common argument of buying a higher megapixel camera is that it would “always” resolve more detail than a lower megapixel camera. That is true but only until you hit the diffraction limit. For example, a full frame camera shot at f/16 will not resolve any detail higher than 8Mp. That is, a 36Mp D800 will not give more details compared to a 12Mp D700 when both are shot at f/16. They both will have an effective resolution of 8Mp only.

To explain this, let us consider a very simple analogy. Notice that when you are driving at night in complete darkness, it is very difficult to distinguish if an incoming vehicle is a small car or a big truck if you were to judge only by their headlights. This is because the apparent separation between the left and right headlights is very dependent on the distance of the vehicle from your position. The headlights seem to look larger and closer together the farther the vehicle is from you. If the vehicle is far enough, both headlights will seem to merge as if there is just one light and you would think it’s a bike instead of a car. The reason is simple: light spreads. Both left and right headlights spread until they seem to merge and by then they become indistinguishable from each other. Diffraction is the same. Diffraction spreads light and you lose the details. Therefore it doesn’t matter if you have two eyes or eight eyes like a spider, you still won’t be able to distinguish two separate headlights if the incoming vehicle is very far. In this case, eight eyes are no better than two eyes. Both sets of eyes still see only one headlight not two. Think of the “number of eyes” as your sensor resolution. It does not matter if you have 8Mp or 2Mp, both cameras will detect only one headlight. Did the 8Mp lose resolution? No. It remained a 8Mp sensor. Did it manage to detect two headlights? No. Therefore in our example, a 8Mp is no better than 2Mp in resolving the number of headlights.

The point is that diffraction destroys details. When there is nothing to resolve, sensor resolution does not matter. Supposing that you have two lines that are very close together, diffraction will spread both lines such that they will appear to merge as if they are just one big line. If you only have one line to resolve it does not matter if you have a 2Mp camera or a 100Mp camera, both will detect only one line. The 100Mp camera will of course have more samples of that single line but it is still just one line. Diffraction does not affect sensor resolving power but it affects how the subject is presented to the sensor. Diffraction blurs the subject in such a way that it limits what the sensor can fully detect.

With that in mind, let us look at practical examples. For a full frame sensor, diffraction at f/8 is enough to blur the subject such that anything higher than approximately 30Mp will not resolve any more details. For each stop, the effective resolution drops by half so at f/11 the limit is 15Mp and at f/16 it’s 8Mp and at f/22 a measly 4Mp. These numbers are just approximations and assume that you have a perfect lens. The reality is much lower than those values.

How about smaller sensors like APS-C or m43? The decrease in resolution is proportional to the crop factor. So an APS-C shot at f/8 will only have a maximum effective resolution of 15Mp while m43 will have 8Mp and so on.

Here are MTF graphs for a Nikon 50/1.4 lens comparing a 16Mp D7000 (crop sensor) with a 36Mp D800 (full frame) at f/5.6 and f/16 respectively. Notice that the resolution at those settings are very similar.


So what are the implications? If you are a landscape photographer with a 36Mp Nikon D800 and you shoot at f/8 or f/11 or maybe f/16 to gain enough depth of field you are basically wasting disk space. At f/8, your 36Mp sensor is no better than a 30Mp sensor. At f/11 it’s no better than a 16Mp D4. At f/16 it is no better than a very old 12Mp D700. So a 36Mp sensor shot at small f-stops is not able to capture enough details and yet the image size remains the same and consumes 36Mp of disk space. If you shoot at f/16 for example, you are better off shooting with a 12Mp D700. If you want to print as big as a 36Mp camera then upsize your 12Mp image in Photoshop to an equivalent of a 36Mp image. Of course the upsized image will not gain any details but it doesn’t matter because the 36Mp hasn’t resolved any more details anyway.

A related analogy is that of scanning photos. Good prints are usually done at 300dpi. When scanning photos, it does not make sense if you scan higher than that because you won’t gain anything. Scanners are capable of 4800dpi or even 7200dpi and maybe higher. If you scan a print at 7200dpi you will get a really huge image but with no more detail than when you scanned it at 4800dpi or lower. You could have just scanned it at 600dpi and you won’t notice any difference. The 7200dpi scan is a waste of time and disk space.

Another common argument is that a sensor with lots of megapixels allows more cropping possibilities. Again, that is true only if you are not diffraction limited. Otherwise you could just shoot with a lower Mp camera, upsize the image and then crop and it will make no difference in terms of details.

This is why I have absolutely no interest in the D800 and other insanely high Mp APS-C cameras like the D7100 and K-3 and A6000. I shoot mostly landscape. I stop down to f/11 and sometimes even to f/22. At those f-stops these cameras are just a waste of space, time and processing power. Again, a 36Mp full frame camera does not make sense unless you shoot mostly wide open at f/5.6 and wider. A 24Mp APS-C is stupid unless you mostly shoot at f/5.6 and wider. Manufacturers keep increasing sensor resolution instead of improving noise performance because most photographers are gullible. Megapixels sell.

Having said that, do not be afraid to shoot at smaller f-stops if the shot calls for it. Even 4Mp effective resolution is a lot if you print at reasonable sizes. And since most people never print at all, 4Mp for web viewing is GIGANTIC!

For a more comprehensive explanation of the effects of diffraction refer to this article: http://www.luminous-landscape.com/tutorials/resolution.shtml

Shoot and shop wisely. 🙂

Debunking Equivalence

What is equivalence? If you haven’t heard of this term used in photography before then don’t bother; you didn’t miss anything. (Part two is here)

If you are curious though, it simply means that different formats or sensor sizes require different settings in order to produce “the same” or equivalent images. Usually, equivalence proponents use the 35mm full frame sensor as the “reference standard”. For example, for a m43 sensor and full frame sensor to have the same angle of view (AoV), the m43 will have to use a 25mm lens and the full frame a 50mm lens because the m43 sensor is smaller; four times smaller to be exact. It doesn’t end there. Since a 25mm lens has a shorter focal length compared to a 50mm there will be differences in depth of field (DoF). The shorter 25mm will have to shoot at f/4 to get the same DoF as a 50mm at f/8.

There are other “parameters” involved in this “equivalence”. For more details, refer to this article in dpreview: http://www.dpreview.com/articles/2666934640/what-is-equivalence-and-why-should-i-care

That dpreview article is funnily entitled “What is equivalence and why should I care”. Should you really care about equivalence? Most photographers don’t care about equivalence. Real photographers’ shooting techniques vary depending on the camera that they brought with them. Give a photographer a mobile phone and he will capture fantastic images without pretending that he is carrying a DSLR. I own a mobile phone, several point-and-shoot cameras, a few m43’s, an APS-C and full frame cameras. I know exactly what each one of them are capable of doing and I shoot accordingly. I don’t expect shallow DoF with my iPhone so every time I shoot portraits with it I need to be careful that the background does not distract from the main subject. Here is an example of how you can capture professional-looking portraits with a simple iPhone 3GS: https://fstoppers.com/editorial/iphone-fashion-shoot-lee-morris-6173.

Bottom line is, gear does not matter. If gear does not matter, equivalence does not matter.

But let’s not stop there. There is more to that equivalence article. To be precise, there are a lot of incorrect information in that article that are very misleading if you are not careful. The biggest misinformation that equivalence proponents spread in forums is that of “total light captured”. I will try to debunk equivalence in the next few paragraphs.

For the sake of example, let’s compare a m43 and a full frame (FF) sensor. By now you should already be aware that a FF sensor is four times larger than a m43 sensor. The m43 crop factor is therefore 2x. It follows that to shoot “the same image” we will have to use different lenses and use different f-stops like so:

m43: 25mm at f/5.6
FF: 50mm at f/11

This will result in the same AoV and DoF. Now what about the rest of the exposure triangle? This is where equivalence-fu starts becoming really stupid. The proponents insist that you could use the same shutter speed for both m43 and FF and still arrive at the same image. They insist that the same shutter speed must be used so that both images will result in the same “blurring” due to subject motion (ROFL!!!). The example above then becomes:

m43: 25mm, f/5.6, 1/125s
FF: 50mm, f/11, 1/125s

Wait, doesn’t that underexpose the FF image? Indeed it does. By two stops, to be exact! Didn’t I say it was stupid? In what world do two images, two stops apart, are considered “the same”? One is obviously darker. Much darker. Equivalence proponents must have something up their sleeves 🙂 You probably guessed it already. They say that you can bump up the ISO of the full frame shot so that it will be of the same brightness as the m43 shot! So now the example becomes:

m43: 25mm, f/5.6, 1/125s, ISO 100
FF: 50mm, f/11, 1/125s, ISO 400

Seriously?!!! Let’s be very clear about this. Bumping up the ISO does not increase light. ISO has absolutely no effect on exposure. Learn about that here. So why do you think that equivalence-fu proponents are suggesting that this ISO bump will make both images equivalent? Their reasoning is quite simple and stupid: because both sensors have gathered “the same total amount of light”!!! Recall that each stop of exposure means twice the amount of light. Since a m43 sensor is four times smaller than a FF sensor it means that underexposing the FF by two stops (4x amount of light) will still result in the same TOTAL light captured by each sensor. If that isn’t stupid then I don’t know what is.

Let’s discuss this further by using a simple experiment. Supposing that we have a m43 camera and we shoot a scene using a 25mm lens. We can produce a full frame equivalent image of the same scene with the same AoV using the same m43 camera by stitching four shots from a 50mm lens. Refer to the illustration below:

Screen Shot 2014-09-28 at 10.31.50 pm

As you can see, the smaller single shot image captured with a 25mm lens will look exactly the same as the larger stitched image which is equivalent to what a full frame sensor would have captured. The narrower AoV of the 50mm lens means that we need four shots stitched side by side to arrive at the same AoV as the 25mm shot. Again, this shows that a FF sensor is four times larger than a m43 sensor. Same AoV, same DoF but different image sizes due to the different sensor sizes.

Now let’s be stupid for a while and assume that equivalence is correct 🙂 In order for the single shot image and the stitched image to have the same total amount of captured light, we will have to underexpose by two stops, each of the four individual shots that we used to stitch the larger image. Since these four images are now much darker we will have to bump their ISO by two stops to arrive at the same brightness as the single shot image. At this point, we now have two “equivalent” images: the smaller, properly exposed m43 image and a larger full frame image that was produced by stitching four underexposed m43 shots.

Common sense will tell you that the larger stitched image is every bit inferior to the single shot image. Two stops inferior to be exact. If you sample a quarter chunk of that larger image it will always turn out much worse than the reference m43 shot. Take a quarter chunk from the top, bottom , sides, or center and every single one of them will look much much inferior to the original properly exposed m43 shot. We can therefore say that the larger image is inherently much inferior compared to the single shot m43 image. So how can equivalence proponents honestly say that the underexposed FF shot is “the same” as a properly exposed m43 shot? You don’t need half a brain to realise that this is plainly stupid.

The stupidity does not stop here though. The equivalence-fu followers have something else to support their “theory”. They suggest that if you print or view the smaller properly exposed m43 image and the larger severely underexposed FF image at the same size, they will look exactly the same. Well maybe they would look the same up to a certain extent. Recall that when you view or print an image at a smaller size than its original size then the effects of downsampling will take effect and will result in a lesser perceived noise: https://dtmateojr.wordpress.com/2014/05/19/megapixel-hallucinations/. This, however, has absolutely got nothing to do with light gathering. As we have shown in our example, the underexposed FF image is much much darker than the reference m43 image if it were not for the ISO bump. Equivalence proponents are using image size to circumvent the destructive effects of underexposure and they think that image size and light are one and the same. Image size has got nothing to do with light. A 41Mp Nokia phone camera has a larger image size compared to a full frame 36Mp D800 although the former has much much lesser total amount of light captured. This is why if you are not careful these equivalence-fu “photographers” will easily mislead you.

Let’s take this circus show to a higher level. Assume that total light and image size are equivalent and related. In that case, we could, in a sense NOT increase the ISO of the underexposed full frame image but instead downsample it to the same size as the m43 image and they should result in the same brightness, right? Simply because the same total amount of light has now been projected into the same image area which should result in the same exposure (total light over total area). But we know that this doesn’t work because downsampling or upsampling has no relationship to total light and that is why the downsampled FF image remains two stops darker. So how could equivalence proponents honestly equate total light and image size? :-O

So now we know that equivalence-fu relies on resampling to work around underexposure. Does this always work? No, it doesn’t. If you recall the discussion in the “Understanding Exposure” article that was linked above, bumping up the ISO does not increase light. It only increases gain. The analogy was that of the process of boiling water. Increasing ISO is like boiling water. Boiling pushes water to the top of the container but it does not increase the amount of water. If you underexpose, you will come to a point where there is no more light being captured. It’s like a container with no water. Bumping the ISO or boiling a container that does not contain water does absolutely nothing. Image noise is more pronounced in darker areas. Underexposure will only worsen the noise in those darker areas. When you have no signal, there is nothing to resample. Downsampling will not always save you.

The nasty effects of bumping up the ISO can not be ignored. Increasing the ISO will also result in hot pixels, banding and other nasty artifacts. Why do you think are cameras limited by how high you can set the ISO sensitivity? Why can’t we not bump the ISO indefinitely? Because the truth is, high ISO sucks regardless of sensor size. Imagine an ISO 6400 shot from a m43 Olympus E-M5 compared to an ISO 25600 shot from a full frame Nikon D800. How much worse does it get if you now compare a point-and-shoot camera with 5x crop factor to that D800. Five stops underexposure is A LOT and really bad. I mean really, try underexposing a night shot on your D800 by 5 stops then bump it up in Photoshop. Crash and burn baby!

If you think that’s bad then consider shooting with slide film. How big is a sheet of film for a 8×10 view camera compared to a measly 35mm camera? For the sake of argument let’s just say that the size difference is 5x. Do you really believe that if I shoot Fuji Velvia on 35mm and then I underexpose Velvia on the 8×10 camera by five stops and push it during development that the images will look “the same”? If this was negative film then maybe you can get away with it but don’t even attempt that kind of circus act with slide film. Slide film is very unforgiving when it comes to exposure. Five stops is almost the entire usable dynamic range of slide film!!! If a photographic “theory” fails miserably with film then that “theory” is simply wrong. In the case of equivalence, it’s bullshit, plain and simple.

So to answer that dpreview article’s question: “should you care about equivalence?”. Not if it’s wrong and stupid.

Update:

I can’t believe that people keep on spreading this nonsense. Here’s another funny equivalence-fu fauxtographer: equivalence for embeciles

Examine his illustration on the effect of different apertures f/8 and f/4. He is totally oblivious to the effect of focal length on light intensity. Note that although f/8 and f/4 here have the same physical aperture size, the longer focal length of the f/8 lens causes the light to be projected much wider into the sensor. The net effect is that each sensel behind the longer f/8 lens receives much lesser number of photons than the sensels behind the shorter f/4 lens. The result is underexposure which is seen as a darker image. Two stops (or 4x light) of underexposure to be exact. This obviously corresponds to noisier sensel output and therefore noisier image.

How can two images with different exposures be equivalent?! Such an idiotic explanation is the result of the epic failure to understand very basic photography. Exposure is totally independent of sensor size. The same f-stop results in the same total number of photons per sensel regardless of imaging format. Always. Same f-stop means same exposure meaning the same brightness.

Child Pornography

This father decided to capture nude photos of his daughter and posted them in the internet. A lot of concerned netizens voiced out their strong opposition against this stupid act and so to prove them wrong, this same father decided to create a gallery exhibit. More info here:

http://petapixel.com/2014/08/22/photographer-accused-of-posting-pornographic-photos-of-his-3-year-old-heres-how-he-responded/

Sorry fucktard but you are a pervert.

There is a VERY BIG DIFFERENCE between capturing CANDID shots and capturing STAGED shots of your innocent NUDE daughter.

Children generally do not care about being nude in front of the public. They do not know of the implications. They are unaware of a lot of things about their bodies. They do not care if they are fat or thin or tall or short. They just don’t care. Let me spell that out: they do not know that their bodies can be used for pleasure. That’s the innocence of a child.

What you just did has corrupted the innocence of your daughter. By stripping her naked and making her pose in front of a camera, you are making her aware that there is something in her nude body that is potentially “interesting”. Interesting not to herself but to YOU, asshole. You need not brainwash a child to appreciate her body. She doesn’t have to. She doesn’t fucking care. But YOU do and you should. It is your duty to protect that innocence. What you did was feed your daughter to other perverts who are possibly worse than you. How many child molesters do you think now have copies of your daughter’s nude photos?

So there!

Having said that, I couldn’t help but compare this act when performed on an adult. It’s the exact opposite. If you shoot a naked adult, who is unaware of your presence, then you have invaded her privacy. Shooting a nude adult who is willing to pose in front of the lens is fair game; she has your full consent.

Know the difference.

You deserved the wrath of the internet.

Blinded By Light

The full frame protagonists are at it again. It’s the same stupid argument. Larger sensor means more TOTAL light gathered therefore lesser noise. Stop the bullshit. Please!!!

In fairness, it’s quite easy to be mislead by this kind of misinformation. If noise is inversely proportional to the amount of gathered light then it makes sense that a larger sensor would result in cleaner photos. Unfortunately, just looking at the total amount gathered light is being very short-sighted. It does not give us the whole picture (no pun intended).

Allow me to explain it again for the nth time. But before that, please read the following articles because they explain this concept in greater detail.

1. https://dtmateojr.wordpress.com/2014/02/28/understand-your-lens-part-3/ — Concentrate on understanding the effect of focal length on light intensity because a lot of people tend to ignore this bit. They are too preoccupied with just the aperture opening maybe because they are more familiar with “fast” lenses without even understanding what “fast” really means.

2. https://dtmateojr.wordpress.com/2014/03/08/debunking-the-myth-of-full-frame-superiority/ — If there is one thing that you’d want to fully understand here, make it the “thought experiment” on dividing a full frame sensor which also explains how shutter curtains work.

3. https://dtmateojr.wordpress.com/2014/06/10/debunking-the-myth-of-full-frame-superiority-part-2/ — This is a good counter-argument to the fact that no two digital sensors are exactly the same even if they are of the same type. A D7000 sensor for example is almost every bit the same as the D800 sensor but because of the improved processing the latter may produce better photos. And so I used film as an example because the same film emulsion will always behave the same way regardless of format (size).

4. https://dtmateojr.wordpress.com/2014/05/19/megapixel-hallucinations/ — Some full frame protagonists insist on comparing ENLARGED APS-C images to full frame equivalents in terms of noise. Of course an enlarged APS-C photo will, for the lack of a better word, enlarge everything including noise. This article debunks that by showing the MATH behind resampling as well as showing samples of real SNR measurements of APS-C and full frame sensors.

5. https://dtmateojr.wordpress.com/2014/04/21/rain-can-teach-us-photography/ — explains what happens in a sensor and why PIXEL size and NOT sensor size matters in greater detail.

6. https://dtmateojr.wordpress.com/2014/05/09/understanding-exposure/ — are for the equivalence clowns who think that they could get away with the bullshit by manipulating ISO. In short, you can’t.

Now if after reading those articles you still need a bigger cluebat then read on…

The biggest mistake that full frame protagonists make is that they equate a sensor to a solar panel. In a solar panel, total light gathered is everything. In a solar panel, every “sensor” contributes to the total energy produced. Of course the bigger the better. Photography though is far from being like a solar panel. Camera sensor pixels are independent of each other. That’s why within an image you will encounter darker parts that are more noisy and blown up parts that have been saturated by light. Each individual pixel receives its own independent number of photons. Pixels can’t share their photons with other pixels. Well sometimes adjacent pixels do “share” photons but this is an undesirable effect called “sensor bloom”. You can see why looking at noise as a result of the total light gathered is wrong. Noise should be examined at the pixel level because this ultimately defines the efficiency of your sensor.

While it is true that a larger sensor gathers more light compared to an APS-C or M43 for the same exposure by virtue of the larger area, this argument is not photographically sound. Photographic exposure is all about LIGHT PER UNIT AREA and not just total light. Saturating a pixel only requires a fixed number of photons. Anything more than that is just wasted light because as soon as a pixel clips then “no data” is presented for processing into an image. An APS-C sensor for example requires half the total amount of light required for a full frame sensor. If you force the same amount of light to both a full frame and APS-C then the latter will oversaturate, i.e. overexpose. It’s like pouring two liters of water into a one liter container. It does not make sense. It is photographically disastrous and plainly stupid. Therefore you get the same noise-free image in an APS-C for half the total amount of light hitting the sensor. Again, you get the same noise-FREE image for HALF the TOTAL amount of light. Again, it’s all about LIGHT PER UNIT AREA and NEVER just total amount of light gathered. It’s all about light intensity.

A smaller area requires lesser incident light. A smaller sensor requires a smaller lens-projected image circle. Smaller image circle is what defines a “crop” sensor or crop lens (e.g. Canon EF vs EFS lenses or Nikon FX vs DX lenses). You crop a full frame image circle just enough to illuminate a smaller sensor. Makes sense?

Unfortunately, there are those that remain blind and they resort to other stupid arguments such as printing at the same size or enlarging a cropped image. Of course a larger sensor is capable of larger prints but this has got nothing to do with light. But let’s be stupid for a minute and assume that a cleaner print is the result of more light gathered during exposure. What happens then if you print at a smaller size? Did you just throw away the light? If not, then where did the light go? If print size has got anything remotely related to light then projecting the same amount of light into a smaller print is like pouring two liters of water into a one liter container so we expect the smaller print to be overexposed, right? But it doesn’t. Because print size has got nothing to do with light and therefore has got nothing to do with noise. The apparent increase in noise when you enlarge a print is NOT the effect of light but the effect of resampling (refer to megapixel hallucination article), i.e. resolution.

In conclusion, total amount of light is just half the truth. The other half is sensor area. Combining both, we get light per unit area otherwise known as photographic exposure. Exposure is what ultimately dictates noise. Smaller area requires lesser light therefore the same exposure results in the same noise profile for different sensor sizes of the same type.

I hope this is the last time I will ever write about this topic. It’s getting long in the tooth and very boring really.

I promise to write a happier article next time. Really. I promise that. 

Megapixel Hallucinations

If you are here to understand (why) equivalence (is wrong) then read this: https://dtmateojr.wordpress.com/2014/09/28/debunking-equivalence/

This post is practically a continuation of one of my controversial posts on debunking the myth of full frame superiority. In that previous post I discussed why full frame is actually no better than it’s crop sensor counterpart (Nikon D7000 vs D800) in terms of light gathering capability. Now I will try to discuss another aspect of full frame superiority and explain why it leads people to believe that it is superior to smaller sensor cameras when in fact it is not.

A common source of sensor performance data is DXOMark. This is where cameras are ranked in terms of SNR, DR, Colour depth, and other relevant aspects of the equipment. It is important to note that data from this website should be properly interpreted instead of just being swallowed whole. This is what I will try to cover in this post.

One of the most highly debated information from DXOMark is that of low light performance which is measured in terms of Signal to Noise Ratio (SNR). SNR is greatly affected by the light gathering capacity of a camera’s sensor and this is why this is commonly used to compare the low light performance of full frame and crop sensors. This is also the most misinterpreted data by full frame owners. They use this information to justify spending three times as much for practically the same camera. Let’s see why this is wrong…

Consider the following SNR measurements between the Nikon D7000 and D800:

Image

Isn’t it quite clear that the Nikon D800 is superior to the D7000? Did I just make a fool of myself with that “myth debunking” post? Fortunately, I did not 🙂 I’m still right. That graph above is a normalised graph. DXOMark is in the business of ranking cameras and that is why they are forced to normalise their data. Let’s have a look at the non-normalised graph to see the actual SNR measurements:

Image

Didn’t I say I was right? 🙂

The Nikon D7000 and D800 have the same low light performance! That is because they have the same type of sensor. The D800 is basically just the D7000 enlarged to full frame proportions. Simple physics does not lie. A lot of “photographers” have called me a fool for that “myth debunking” post. Well, I’m not in the business of educating those who are very narrow-minded so I will let them keep believing what they believe is true. But some of us know better, right? 🙂

Let’s not stop here. Allow me to explain why the normalised graphs are like that.

Let me tell you right now that DXOMark is unintentionally favouring more megapixels. That’s just the inevitable consequence of normalisation. Unfortunately, those who do not understand normalisation use this flaw to spread nonsense. The normalised graphs are not the real measured SNR values but are computed values based on a 8Mp print size of approximately 8×10. The formula is as follows:

nSNR = SNR + 20 x log10(sqrt(N1/N2))

where nSNR is the normalised SNR, N1 is the original image size and N2 is the chosen print size for normalisation. In the case of the Nikon D800, N1 = 36Mp and for the D7000, N1 = 16Mp. They are both normalised to a print size of N2 = 8Mp. Based on that formula, the D800 has a SNR improvement of 44.93 up from measured SNR of 38.4. The D7000 though only improves a tiny bit to 41 up from 38. As you can see, although both cameras started equally, the normalised values have now favoured the D800.

This increase in SNR is not because the D800 has better light gathering capability. This apparent increase in SNR is due to downsampling. It’s due to the larger image size and not because of better light gathering capability. Unfortunately, this computed SNR is what the full frame fanbois are trying to sell to uninformed crop sensor users. It is the REAL measured SNR that matters and we will learn later on how important this is compared to just more megapickles.

Go back to that normalisation formula and note the term inside the square root (N1 / N2). Note that if N1 is greater than N2 then the log10 becomes a positive number and the whole term adds to the measured SNR. The term drops to zero for N1 = N2 and that’s why when a D800 image is printed at 36Mp, the SNR is the measured SNR. Same goes for the D7000 when printed at 16Mp. That is why when I blogged about noise performance comparisons I kept repeating that images should be printed at their intended sizes. That’s the ONLY fair comparison. Downsampling is cheating. You do not want to buy a 36Mp camera so you could print it at 8×10. That is an absolute WASTE of money.

The idiots will of course justify by saying “well the good thing with having a larger image is that you can downsample and it will outperform a smaller image“. Well not so fast, young grasshopper. That is not true. We know that SENSEL size generally results in better light gathering capacity (Rain Can Teach Us Photography) although this means smaller image size. Let’s consider the D800 vs D4:

Image

So the real SNR shows the D4 (42.3) being superior compared to the D800 (38.4). Again, when normalised to a 8Mp print, the D800 somehow “catches up”:

Image

Unfair isn’t it? Well, only for smaller prints. Using the same formula to compute the SNR in a 16Mp print, the D4 drops to its real measured SNR of 42.3 while D800 SNR drops to 41.92. So now the D800 is inferior to the D4! How about for a 36Mp print? The D4 drops to 38.77 and the D800 drops to its real measured SNR of 38.4. The 16Mp D4 upsized to a whooping 36Mp print BEATS the D800 in its own game!!!

In the comparison above between two full frame cameras we see that even if the total amount of light, which is proportional to the sensor size, does not change, variations in SNR can occur if resampling is added into the equation. Clearly, total light and resampling are unrelated. Just because one sensor has better noise performance at a given print size does not imply that it has better light gathering capacity. If 8Mp was the only print size we could make, one would think that the D800 is every bit as good as the D4. This is clearly not the case at larger print sizes where the D4 outshines the D800. The same argument can be said for comparisons between sensors of different sizes. Sensor performance should not be judged based on arbitrary print sizes. Sensor performance must be taken at the sensor level. 

Think about it: every time you print smaller than 36Mp, you are WASTING your D800. Who consistently prints larger than 16Mp or even 12Mp? As you can see, the superior 16Mp sensor makes a lot more sense. The D800 is a waste of space, time, and money.

In essence, a 16Mp sensor, be it full frame or crop can beat the 36Mp D800 if it has high enough SNR. The crop sensor need not match the superior D4 sensor. A 16Mp crop sensor with the same SNR performance as the 7-year old Nikon D700 will beat the D800 at print sizes of 16Mp and higher.

Let’s summarise what we have covered so far:

0. DXOMark data needs to be analysed. Better SNR performance in normalised data does NOT imply better light gathering capacity of full frame sensors but merely a consequence of larger image size in terms of megapixels.

1. DXOMark normalises their data because they are in the business of ranking cameras.

2. Normalisation to a small print size unintentionally favours sensors with more megapixels.

3. More megapixel does not necessarily lead to superior SNR when downsampled.

4. At larger prints (16Mp and higher), the weakness of the 36Mp D800 sensor begins to show.

5. A good quality crop sensor camera with lesser megapixels can beat a full frame camera with insane megapixels.

Do you believe me now?