Wow, that's quite interesting.
However, a part of that discussion post that caught my eye was this:
Quote:
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After registering I make an ImageIntegration of all the registered images. Use equal weight (1:1) and disable normalization. The monochrome registered images has to be converted to RGB first. Because not all images cover the full field of the TransformMaster, you will get vignetting towards the edge of the image. This is where the masks come in handy. First integrate all of them again using 1:1 weight and no normalization. Then you use the stacked masks as a “flat frame”. In PixelMath you make a simple formula: RGB_Integration/Masks_Integration, and create a new image using that. The result is a perfectly flat field.
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If I get a bit more data for M16, I might be able to try this approach on it.