bobn2
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f-number equivalent between m43 and FF
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Great Bustard
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What is the purpose of comparing at the same enlargement? We would compare at the same display size. Thus, the 50mm crop would be enlarged 2x more than the 100mm photo.
As I said, why in the world would we compare the noise of two photos at different display sizes? That said, the visible noise will depend on the total amount of light that fell on the sensor and the sensor efficiency.
You are wrong, sir. Take the photos and post them at the same size.
In fact, it is you who are mixed up by wanting to compare the noise in photos at different display sizes. It is exactly the same fallacy as claiming that a lens that resolves 60 lp/mm on one sensor outresolves a lens that resolves 40 lp/mm on a sensor twice the size.
But the total amount of light making up the 50mm crop is 1/4 as much as the total amount of light making up the 100mm photo.
Take the photos. Post them. Guess what?
Great Bustard
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Can you go into more detail as to what the posted photos are? Thanks!SD9, LO res, ISO 400, 70mm vs 35mm (zoom marks):
Noise display by ImageJ
Any conclusions to be drawn from this? GB? DC?
bobn2
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You're effectively measuring the camera pixel variation, so you're not measuring the noise at the same final image size.SD9, LO res, ISO 400, 70mm vs 35mm (zoom marks):
Noise display by ImageJ
Any conclusions to be drawn from this? GB? DC?
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Bob
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Great Bustard
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Actually, the question comes up a decent amount with regards to APS-C vs FF.
It doesn't. It's also not relevant, except inasmuch as the pixel count affects sensor efficiency. For example, if we had two sensors, one with 12 MP and the other with 24 MP with the same size and same QE, then if the read noise per pixel were the same for each sensor, the 24 MP sensor would be more noisy (although this would only be apparent in very low light).
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Allan Olesen
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Let us compare the Nikon D800 (FF, 36MP) and the Nikon D7000 (APS-C, 16MP).
Same pixel size. Same Sony sensor technology. Same noise per pixel if you expose equally (same f-stop, shutter speed and scene light).
But not same magnification of the final output.
If you take the same photo with these two cameras and enlarge to the same output size, each pixel from the D7000 will be magnified 1.5x more in each direction. Consequently, the final output will appear more noisy.
And you can't really say I am wrong about that because I am actually just repeating your own claims from another post in this thread: The same pixel will look more noisy the more you magnify it.
So yes, it is all about sensor area.
dwalby
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I agree its all about sensor area, but I'm not sure I agree with your example.
In the case of two sensors of different size, but with the same size pixel, you have the same SNR for each pixel, we all agree on that.
Where I don't necessarily agree with you is that the simple act of printing the pixel larger or smaller will have any effect on its SNR. Back to the blue sky example, if you have high per pixel SNR a field of blue pixels will have a more uniform set of values than something with a lower per pixel SNR, and appear less noisy, because it is. But in the case you describe, where the per pixel SNRs are equal, the difference in adjacent pixel values due to the noise will be the same, the only difference is how far apart those differences are spaced on the print. So I think in your example the 36MP image will have the same noise as the 16MP image regardless of how large each is printed. The main difference will be in the resolution of the 36M image being able to print finer detail than the 16MP image. The pixels themselves don't get any noisier simply by being enlarged to print over a larger print area.
What I'm not sure about though, is if seeing the pixel-to-pixel noise variation spaced closer together in the 36MP print, as opposed to further apart in the 16MP print, produces a result that appears to have less noise to the eye when viewing the prints. I've never experimented with that to have an opinion, so if that's the case I won't try to argue that, but I would still claim that the per pixel SNR continues to be the same regardless of magnification. The value of the pixel remains the same regardless of how large you print that pixel, so I'd argue because of that its impossible to make it more noisy simply by printing it bigger.
In the case of two sensors of different size, with the same number of MP, then the larger sensor will have more area/pixel, more photons/pixel, and therefore higher SNR per pixel. I think we probably agree on that, in which case both prints at the same size will favor the larger sensor due to the higher SNR of its pixels.
bobn2
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Allan Olesen
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Yes.
I have never claimed that.
I have claimed that it will have an effect on the visibility of the noise.
And instead of writing all those words, do a simple experiment:
Take a photo of a blue sky. Zoom in to 100% and notice the noise. Then zoom in to 200% and notice the noise getting much more visible.
Same pixels, same noise per pixel, just magnified more. Result: More visible noise.
dwalby
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OK, so we're in agreement. I'm at work, writing words kills time waiting for simulations to finish, so its no big deal. In my prior post I suggested that what you meant was 'visibility' of the noise, not the mathematical measurement of the noise, so thanks for confirming that.
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Great Bustard
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It's not all about sensor area -- it's all about the total amount of light falling on the sensor and the efficiency of the sensor.
What does per-pixel SNR have to do with the noise in the photo?
Take a picture of the sky at, for example, 50mm f/5.6 1/400 ISO 100 and 100mm f/5.6 1/400 ISO 100. Crop the 50mm photo to the same framing as the 100mm photo. Display both at the same size. Which photo is more noisy?
Which do you think is more noisy? The photo below:
or a 100% crop of it displayed at the same dimensions?
The larger sensor will have less noise than the smaller sensor regardless of pixel count for a given exposure and sensor efficiency.
dwalby
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a pixel has a signal level, as measured by the A/D converter, and an uncertainty due to noise. Divide the signal by the noise and you have SNR. If you have a 1-pixel sensor and take several images at the same exposure, you'll get variations in the result that are consistent with that SNR.
Allan Olesen
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In my first post in this thread I used the exact words "appear more noisy". I can't see why you need a confirmation.
Just to sum up:
Looking isolated at pixel size does not say anything about the appearance of noise in a photo.
Looking isolated at per pixel noise does not say anything about the appearance of noise in a photo.
If you want to know something about the appeareance of noise, you need to look both at pixel size and per pixel noise.
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dwalby
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Because printing an image with a lower SNR would also 'appear more noisy' when compared to one printed with a higher SNR. I didn't think you meant the SNR had changed, but you didn't say one way or the other, so I simply asked a question. You seem to be rather irritated by the whole thing, I'm sorry I asked.
bobn2
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Wrong. A pixel has a signal level as measured by the A/D converter. That is all, it gives a single value.
They are crops from pictures of my wellhouse, the which pictures were taken according to your suggestion quoted above.Can you go into more detail as to what the posted photos are? Thanks!SD9, LO res, ISO 400, 70mm vs 35mm (zoom marks):
Noise display by ImageJ
Any conclusions to be drawn from this? GB? DC?
I took a photo of the scene at 35mm f/8 1/350 ISO 400 and another photo of the same scene from the same position at 70mm f/8 1/350 ISO 400. Displayed both photos at the same subject magnification in FastStone Viewer's comparison window (the smaller image zoomed in but not smoothed). Took a screen capture ('Untitled-2') and opened it in ImageJ and took a histogram for each dark area, then screen-captured again for posting. Best viewed full size, of course. The bell curves should tell the story, do we think. The standard deviation at left being 40% of the mean, at right being 32% of the mean, what does that tell us?
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dwalby
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Great Bustard
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The amount of light falling on the pixel during the exposure is subject to uncertainty, due to the nature of light itself. This is known as photon noise. Then the sensor adds additional noise, which is called read noise.
Bob is saying that a single pixel does not have noise, because he is computing the noise by taking the average value of a patch of pixels that should have uniform values and computing the standard deviation.
However, we could compute the noise of a single pixel by instead taking several identical exposures, recording the values of a pixel, computing the mean, and then the standard deviation.
Regardless, it is *crucial* to understand that noise comes from the light itself (photon noise), and that this noise is an inherent property of the light, having nothing, whatsoever, to do with technology. The sensor and supporting hardware then adds in additional noise (read noise).
Except for the portions of the photo where the light is very low, the photon noise is the dominant source of noise. Thus, for deep shadows and/or very high ISO photography, the read noise becomes an important factor, but until that point, it is the photon noise that is dominant.
Either way, it is not per-pixel noise that matters, but image noise, and this is a function of the total amount of light falling on the sensor (and sensor efficiency), not the amount of light falling on a single pixel.
Great Bustard
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Do the crops show equal portions of the scene, or are they 100% crops?They are crops from pictures of my wellhouse, the which pictures were taken according to your suggestion quoted above.Can you go into more detail as to what the posted photos are? Thanks!SD9, LO res, ISO 400, 70mm vs 35mm (zoom marks):
Noise display by ImageJ
Any conclusions to be drawn from this? GB? DC?
When you say "same subject magnification", does that mean 100% view, or, for example, each crop showing 1% of the scene?
I can answer that when I have answers to the two questions above.
dwalby
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Yes, I know that, it just wasn't important in the context of the original discussion regarding SNR being attributable to a single pixel. I was only discussing the basic concept of noise being present, not the nature of the noise itself.
Well, Bob could have said that, but he seemed happier with one-sentence answers with no details. Computing the stdev of multiple pixels does not invalidate the assumption that an individual pixel can have an SNR value associated with it, it just changes the SNR computation.
exactly, which is what I said earlier about having a 1 pixel sensor, then exposing it multiple times at the same exposure setting and seeing how the pixel value varied with each exposure.
again, already understood. I believe the noise distribution is Poisson when a very small number of photons are counted, and becomes Gaussian when a larger number of photons are counted. And as such, if the signal voltage created by the photons is S, the noise voltage (standard deviation) is the square root of S.
And, in the example above regarding averaging a patch of pixels, the average sum of N signal voltage values is NS and the standard deviation increases as the square root of N.
Please correct me if I'm wrong in any of these comments.
agreed, never challenged this.
Bob stated that a single pixel doesn't have an SNR, I disagreed with that claim. Everything you said above is true, and I agree with, it just wasn't part of the original claim I disputed.
I'm not disputing whether or not per-pixel SNR is the best metric for evaluation of a sensor's performance, I was simply stating that it is possible to measure and compare the SNR of a single pixel on any given sensor. Perhaps if Bob had taken the time to explain his own comments a little more thoroughly you wouldn't have had to do it for him.
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