I'll do a comparison on my Raw files tomorrow, between an exposure pair and the 2 single file sub-channels.

I have extracted a center crop (200x200px) of the G1 channel from 2 files from my Canon EOS-1Ds3, extracted via DCRaw as undemosaiced Raw data numbers and split with ImageJ into separate channel files. It was verified that the channel files represent the same data numbers as RawDigger gives for the same sensel positions. Then the same Auto Blackpoints have been subtracted as RawDigger does.

ID=142_G1_BPC1023, Min=12601, Max=13411, Mean=13005.046, StdDev=93.598

ID=143_G1_BPC1023, Min=12757, Max=13539, Mean=13143.038, StdDev=95.265

Mathematically, if they are truly

*Random* and

*Independent* samples from a Normal distribution, one could expect a more accurate average noise estimate to be Sqrt((93.598^2+95.265^2))/Sqrt(2) = 94.435 for these two samples from the same noisy distribution.

However, when we actually subtract the channels of 2 files and take the statistics from that result we get:

Min=-492, Max=212, Mean=-137.991, StdDev=80.857 . That lower StdDev suggests that there is a non-random component in the data which reduces the Standard Deviation. To get the actual noise level we still need to divide by Sqrt(2).

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Repeating that for the G2 channel from 2 files:

ID=142_G2_BPC1024, Min=12470, Max=13212, Mean=12864.084, StdDev=92.014

ID=143_G2_BPC1024, Min=12607, Max=13392, Mean=12999.766, StdDev=92.694

Again, mathematically, if they are truely Random and Independent samples from a Normal distribution, one could expect a

more accurate average noise estimate to be Sqrt((92.014^2+92.694^2))/Sqrt(2) = 92.355 .

However, when we actually subtract the channels of 2 files and take the statistics from that result we get:

Min=-527, Max=242, Mean=-135.682, StdDev=79.093 . That also suggests that there is a non-random component in the data which reduces the Standard Deviation. To get the actual noise level we still need to divide by Sqrt(2).

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Now repeating that for the subtraction of the G1 and G2 channels in a single file, which may be not truely independent and may have some PRNU added to the Normal distribution noise:

ID=142_G1-G2_BPC, Min=-378, Max=638, Mean=140.963, AvgStdDev=123.317, CorrectedStdDev=87.198

and

ID=143_G1-G2_BPC, Min=-407, Max=652, Mean=143.272, AvgStdDev=124.258, CorrectedStdDev=87.864

That shows a Standard deviation that is indeed closer to the proper subtraction of exactly the same sensel positions, but not quite as low. I've added the four 16-bit TIFF files of the Black-point adjusted center-crops for experimentation, and the histograms of the single file G1-G2 subtractions for information.

I'm not exactly sure yet how to correlate that to the sample positions offset or PRNU, maybe I need to try with more samples to test it in practice.

Cheers,

Bart