More E-PL3 noise results...

Last night, I took some more dark frames to try to characterize the noise.  Selecting only the "warm" pixels from the 60s dark frame that I analyzed in the last post, I looked at the signal distribution from those same pixels in a sequence of dark frames with exposures from 30 seconds to 1 second.  The first figure shows that the mean and width of the warm pixel distribution scales with exposure time, and that (based on the 30s exposure) the selected pixel population comprehensively captures the pixels making up the warm pixel population in all exposures.  In other words, the problem pixels are a fixed population.  Furthermore, with this data set, I find that the mean of the warm pixel distribution is linear in time (see 2nd figure).

Warm pixel signal (selected from 60s dark frame) for a sequence of shorter exposure dark frames.  The blue histogram is the full distribution (all pixels) from the 30 s dark.  Note that the selected pixels from the 30 s fill the anomalous noise peak of the full distribution.  This shows that the problem pixels are a fixed population.

The other quick experiment I did was to take three 60 s darks in sequence.  This time, I'm showing the full distributions with the Y-axis log scaled.  Between the first and second dark frames shown here, I took a few shorter dark frames.  The second and third are taken directly sequentially.  The data here shows that the mean of the warm pixel distribution (dark current) is temperature dependent.  This is not a surprising result, except that for the bulk of the pixels, the signal stays put at ~64 ADU, though the main peak does broaden for the later frames.

The upshot of this analysis is that "noise reduction" via subtraction of a dark frame taken immediately after the image is the best way to combat this noise.  The 1-30 second sequence indicates that this becomes important for exposures longer than 8 seconds, though this should be taken as a temperature-dependent statement.

Another interesting note (not shown here, so you'll have to take my word for it).  Within the warm pixel distribution, the noise appears to be uncorrelated.  That is, if I subtract the signals from two frames, the width of the difference's distribution is the quadrature sum of the two distributions.

One more interesting note:  I would expect the variance of the distributions to scale linearly in time, but it does not.  It's faster than linear.  I can't explain right now.