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Pattern error in D810 dark-field images

November 9, 2014 JimK Leave a Comment

I’ve been analyzing the low-frequency behavior of read noise in several cameras for the last two weeks. Now I turn my attention to how much of the dark-field images vary from exposure to exposure, and how much form a fixed pattern. In addition, I will explore the differences in the spatial spectra of the fixed and variable parts of the dark-field image.

The camera I’ve chosen for my first set of experiments is the Nikon D810, I started by making a series of dark-field exposures at ISO 1000 and 1/8000 second. I chose ISO 1000 because that is the ISO where the D810 just starts to clip the left side of the dark-field histogram. It is also the highest ISO on the camera that has no digital gain applied.

I made 256 exposures, and averaged the raw images (all four channels), recording the standard deviation of the averaged image after each exposure was averaged in:

D810averaging

You can see that the curve flattens out after about 128 images in the average, which means that there’s a portion of the dark-field image that doesn’t vary from frame to frame.

Want to see it in electrons? Sure thing:

 

D810averagingE

The electron count of the curve’s intercept with the left axis may be bigger than you’re used to seeing. That’s because I took the standard deviation of the entire frame, not of a small crop.

Then I took one of the dark-field images and measured the way that the standard deviation varied with averaging kernels of three shapes (one dimensional horizontal, one dimensional vertical, and square) and many sizes:

d810rnlpnosub

You can see that the curves flatten out, indicating that there the spatial frequency content of the dark-field image is not flat, or white, but that there is more low frequency content than would be in an image with a flat frequency spectrum.

I performed the same set of calculations after subtracting the average of 256 frames from the dark-field image:

d810rnlpsub

Now there is very little flattening of the curves — although there is some with the largest vertical kernels — indicating that the corrected image has very little additional low-frequency content over that of an image whose noise is white.

We can get another angle on it by processing the averaged image:

d810rnlp256avg

Yes, indeed. That’s where the low frequency content is. Middle frequency, too, look how the curves start to flatten for even very small kernels.

It looks like almost all the low-frequency “read noise” of the D810 can be eliminated with the subtraction of a reference image.  You deep-sky photographers might want to take note of that.

 

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