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Hi all, hopefully some of the mods or experienced users will have time to take a look at the issue. I am dealing with a few datasets as shown on the slide below.
Sets 1 and 2 are from several sessions, which I have stacked together independently. Set 3 is from a single session, quality is bad due to absence of calibration frames.
Questions:
- Should I expect an improvement of SNR (general visual clarity) if I stack sets 1 and 2 with default settings and high LNC and MBB? I have tried it and result seem to be worse than stack of set 1 -- less contrast, unnatural colours, overall washed out look.
- Will the result be better if I combine raw subs and stack everything in one go instead of stacking material from two sources separately and then stack the results as lights?
- What's the best way to add stack 3 to the mix so that it is not ignored by the algorithm? I've tried to stack set 2 and set 3 and the result was basically the same as set 2 (see below). I did set the reference frame manually to the higher res. set 3 image.
Looking forward to your replies.
Good questions, yet a bit tricky to answer. The datasets are very different in quality and I think combining those will result in a worse result than the one that looks the best. If the datasets with lots of noise etc. are added, that will make it worse and the SNR will likely drop. The reason is that you add data in which any signal is mainly in the noisy part of that data. For these situations I tend to separate datasets based on quality and stack them as separate results. To get better results with different setups, you'd need to get those better. Set 2 for example, with a slow lens, requires longer exposures per sub to get the signal out of the background better.
