... ignoring the pattern noise. And that is the solution to the puzzle.
But can you actually compute pattern noise as a separated entity?
Doesn't seem so easy.
There are several ways one can use, to get an idea you can push D3X
file shot at ISO 100 10eV in a converter.
To return to the discussion, the key think about quantitative
measurements is to measure things that are subjectively important.
If pattern noise is subjectively important, ways can be found to
measure it. Returning to the MR's audio analogy, the problem with
audio testing wasn't that it was quatitative, but that it was testing
things that weren't subjectively important. It turned out that TID
was much more subjectively important that THD, and that it also
helped to know the distribution of harmonics in the distortion.
The key to measuring 'pattern noise' is in the word 'pattern'. Random
noise has a known (spatial) frequency distribution. Noise that has
other distributions is pattern noise, so a noise spectrum would give
a fair indication of the relative strength of random and pattern
noise, and some clues about the nature of the pattern noise. With
some research, it might also be possible to quantify the
objectionableness of different frequency distributions.