September 01, 2015, 08:26:00 PM

Author Topic: So sayeth DXO: "The a7R II poops on the 5DS"  (Read 5050 times)

privatebydesign

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Re: Sony A7R II scores 98, new king of DxO Mark (by a nose)
« Reply #60 on: Today at 12:11:32 PM »
You are not averaging, you are adding, to get the lower noise you have to divide by the number of pixels you have added together, in this case four. Take any one pixel of information and it has to fit in the bit depth, for 14 bit that is 16,385, if you add four together you can't have a number higher than 16,385, so you have to divide by that same number to keep your range constant.

So take your last block of four, if noise becomes visible, your noise floor, at 3 (for example) you have two noisy pixels px-ID-14 and px-ID-15, if you add the four together you get 8, then divide by four you get 2 per pixel, which you can't see. Voila, two pixels that had visible noise don't now have visible noise, but you have lost the ability to differentiate detail in those four pixels so you now have one noiseless pixel instead of two of four noisy ones.

To be sure, your DR has not increased in that you don't have a wider range, you can't see below your noise floor and the bit depth has not increased because add four and divide by four is a zero sum when confined to whole numbers. You have lowered the noise levels by averaging/downsampling though.
Hi PBD, thanks for the reply.

I don't know if I'm just retarded, but I still don't get it. I included a division process in the averaging my original spreadsheet here is an update I just changed the layout to put the averages in at the bottom of the table (see attached)

Is my concept of average image noise flawed (i.e. Average image noise = sum of pixel noise divided by number of pixels)

Yes, you don't average the first group.

So take your first four pixels, say the noise floor is 4, ID-2 and ID-4 are both noisy pixels, at 100% view those pixels are garbage. Add the four together and divide by four and the resulting value is 3, so that block of four pixels, that is now one number is no longer noisy, at 100% view that down sampled one pixel (the four have become one) is not noisy but the picture is 1/4 the size it was.

This is how multiple exposures reduces noise on a same size basis, take various exposures of the same thing, add them together and divide by the number of exposures and you get less noise and retain the number of pixels. Basic astrphotography.

Quote
Is my concept of average image noise flawed (i.e. Average image noise = sum of pixel noise divided by number of pixels)

Yes this concept is wrong. Remember, you are not adding up all the values and dividing by the total number of pixels, you are only adding the down sampled pixels together and dividing by that number of pixels to get a new averaged pixel value. Then the number of actual pixels that fall into the range of noise is lower, but so is detail!

P.S. You can't have decimal places in your averages (you'd need more bit depth), so in the adjusted table below the .5 and above would be rounded up, .49 and lower would be rounded down. So you'd actually have 6 - 3 - 1.
« Last Edit: Today at 12:36:30 PM by privatebydesign »
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Re: Sony A7R II scores 98, new king of DxO Mark (by a nose)
« Reply #60 on: Today at 12:11:32 PM »

StudentOfLight

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Re: Sony A7R II scores 98, new king of DxO Mark (by a nose)
« Reply #61 on: Today at 12:23:35 PM »
You are not averaging, you are adding, to get the lower noise you have to divide by the number of pixels you have added together, in this case four. Take any one pixel of information and it has to fit in the bit depth, for 14 bit that is 16,385, if you add four together you can't have a number higher than 16,385, so you have to divide by that same number to keep your range constant.

So take your last block of four, if noise becomes visible, your noise floor, at 3 (for example) you have two noisy pixels px-ID-14 and px-ID-15, if you add the four together you get 8, then divide by four you get 2 per pixel, which you can't see. Voila, two pixels that had visible noise don't now have visible noise, but you have lost the ability to differentiate detail in those four pixels so you now have one noiseless pixel instead of two of four noisy ones.

To be sure, your DR has not increased in that you don't have a wider range, you can't see below your noise floor and the bit depth has not increased because add four and divide by four is a zero sum when confined to whole numbers. You have lowered the noise levels by averaging/downsampling though.
Hi PBD, thanks for the reply.

I don't know if I'm just retarded, but I still don't get it. I included a division process in the averaging my original spreadsheet here is an update I just changed the layout to put the averages in at the bottom of the table (see attached)

Is my concept of average image noise flawed (i.e. Average image noise = sum of pixel noise divided by number of pixels)

Yes, you don't average the first group.

So take your first four pixels, say the noise floor is 4, ID-2 and ID-4 are both noisy pixels, at 100% view those pixels are garbage. Add the four together and divide by four and the resulting value is 3, so that block of four pixels, that is now one number is no longer noisy, at 100% view that down sampled one pixel (the four have become one) is not noisy but the picture is 1/4 the size it was.

This is how multiple exposures reduces noise on a same size basis, take various exposures of the same thing, add them together and divide by the number of exposures and you get less noise and retain the number of pixels. Basic astrophotography.
I've ask the question before in a different thread regarding how "noise floor" is calculated but unfortunately got no reply. I thought that since this example is a dark frame that the average value of all the "supposed-to-be-zero-value pixels" would be the noise floor. Hence I calculated the average value of 2.5 initially.
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privatebydesign

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Re: Sony A7R II scores 98, new king of DxO Mark (by a nose)
« Reply #62 on: Today at 12:46:16 PM »
You are not averaging, you are adding, to get the lower noise you have to divide by the number of pixels you have added together, in this case four. Take any one pixel of information and it has to fit in the bit depth, for 14 bit that is 16,385, if you add four together you can't have a number higher than 16,385, so you have to divide by that same number to keep your range constant.

So take your last block of four, if noise becomes visible, your noise floor, at 3 (for example) you have two noisy pixels px-ID-14 and px-ID-15, if you add the four together you get 8, then divide by four you get 2 per pixel, which you can't see. Voila, two pixels that had visible noise don't now have visible noise, but you have lost the ability to differentiate detail in those four pixels so you now have one noiseless pixel instead of two of four noisy ones.

To be sure, your DR has not increased in that you don't have a wider range, you can't see below your noise floor and the bit depth has not increased because add four and divide by four is a zero sum when confined to whole numbers. You have lowered the noise levels by averaging/downsampling though.
Hi PBD, thanks for the reply.

I don't know if I'm just retarded, but I still don't get it. I included a division process in the averaging my original spreadsheet here is an update I just changed the layout to put the averages in at the bottom of the table (see attached)

Is my concept of average image noise flawed (i.e. Average image noise = sum of pixel noise divided by number of pixels)

Yes, you don't average the first group.

So take your first four pixels, say the noise floor is 4, ID-2 and ID-4 are both noisy pixels, at 100% view those pixels are garbage. Add the four together and divide by four and the resulting value is 3, so that block of four pixels, that is now one number is no longer noisy, at 100% view that down sampled one pixel (the four have become one) is not noisy but the picture is 1/4 the size it was.

This is how multiple exposures reduces noise on a same size basis, take various exposures of the same thing, add them together and divide by the number of exposures and you get less noise and retain the number of pixels. Basic astrophotography.
I've ask the question before in a different thread regarding how "noise floor" is calculated but unfortunately got no reply. I thought that since this example is a dark frame that the average value of all the "supposed-to-be-zero-value pixels" would be the noise floor. Hence I calculated the average value of 2.5 initially.

My understanding is that noise floor is a comparatively arbitrary figure given as a percentage of signal. That is, anything below X value and above 0 is noise, so in your examples above it would be more accurate to say anything any pixel value between 1 and 3 would be considered noisy, but the averaging works just the same, you get less noisy pixels and fewer of them. So in the imaginary simplified version we are using 0 is black, 4 is the darkest grey you can discern, 1-3 are just noise.

Forgive me for keep having edited my above reply whilst you were replying to it!
Too often we lose sight of the fact that photography is about capturing light, if we have the ability to take control of that light then we grow exponentially as photographers. More often than not the image is not about lens speed, sensor size, MP's or AF, it is about the light.

bedford

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Re: Sony A7R II scores 98, new king of DxO Mark (by a nose)
« Reply #63 on: Today at 01:06:28 PM »
I've ask the question before in a different thread regarding how "noise floor" is calculated but unfortunately got no reply. I thought that since this example is a dark frame that the average value of all the "supposed-to-be-zero-value pixels" would be the noise floor. Hence I calculated the average value of 2.5 initially.

The noise is not the average value, but the arbitrary deviation of the values.

If you calculate the relevant statistical values for your example:
Number of pixels 16 ==> avg = 2,5; standard deviation = 2,221
Number of pixels 8 ==> avg = 5; standard deviation = 2,268
Number of pixels 4 ==> avg = 10; standard deviation = 3,65 (althoug not very meaningful, because the number of pixels is too low)

Average calculates as (sum of values)/(number of values).

Now, if you take avg/StdDev as measure for the signal-to-noise ratio you will see, that the lower the number of pixel the higher the SNR.

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Re: Sony A7R II scores 98, new king of DxO Mark (by a nose)
« Reply #64 on: Today at 06:13:54 PM »
You are not averaging, you are adding, to get the lower noise you have to divide by the number of pixels you have added together, in this case four. Take any one pixel of information and it has to fit in the bit depth, for 14 bit that is 16,385, if you add four together you can't have a number higher than 16,385, so you have to divide by that same number to keep your range constant.

So take your last block of four, if noise becomes visible, your noise floor, at 3 (for example) you have two noisy pixels px-ID-14 and px-ID-15, if you add the four together you get 8, then divide by four you get 2 per pixel, which you can't see. Voila, two pixels that had visible noise don't now have visible noise, but you have lost the ability to differentiate detail in those four pixels so you now have one noiseless pixel instead of two of four noisy ones.

To be sure, your DR has not increased in that you don't have a wider range, you can't see below your noise floor and the bit depth has not increased because add four and divide by four is a zero sum when confined to whole numbers. You have lowered the noise levels by averaging/downsampling though.
Hi PBD, thanks for the reply.

I don't know if I'm just retarded, but I still don't get it. I included a division process in the averaging my original spreadsheet here is an update I just changed the layout to put the averages in at the bottom of the table (see attached)

Is my concept of average image noise flawed (i.e. Average image noise = sum of pixel noise divided by number of pixels)

Yes, you don't average the first group.

So take your first four pixels, say the noise floor is 4, ID-2 and ID-4 are both noisy pixels, at 100% view those pixels are garbage. Add the four together and divide by four and the resulting value is 3, so that block of four pixels, that is now one number is no longer noisy, at 100% view that down sampled one pixel (the four have become one) is not noisy but the picture is 1/4 the size it was.

This is how multiple exposures reduces noise on a same size basis, take various exposures of the same thing, add them together and divide by the number of exposures and you get less noise and retain the number of pixels. Basic astrophotography.
I've ask the question before in a different thread regarding how "noise floor" is calculated but unfortunately got no reply. I thought that since this example is a dark frame that the average value of all the "supposed-to-be-zero-value pixels" would be the noise floor. Hence I calculated the average value of 2.5 initially.

It's very commonly defined as SNR=1
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Re: Sony A7R II scores 98, new king of DxO Mark (by a nose)
« Reply #64 on: Today at 06:13:54 PM »