[codemonkey (Lee)]

Originally Posted by peter_4059

I think you need to compare 50x1 min subs to 10x5 min and see which one looks cleaner. I suspect the 10x5 stack is going to have the higher SNR and look cleaner.

Yeah, that's the plan. Actually, the original plan was to take a crazy amount of very short subs (~5s) and compare, but it becomes very difficult to register narrowband subs of that length.

Originally Posted by RickS

My experience is that things work in practice pretty much as expected in theory and that higher SNR images look better. Not sure what has happened with your experiment but I wouldn't jump to any conclusions

Noise is random and hard to estimate accurately unless you have a statistically significant number of samples.

Cheers,
Rick.

Fair enough, thanks for your thoughts, Rick.

Originally Posted by Slawomir

Hi Lee,

STF will stretch different data differently, and from what you wrote I gather you just applied STF 3 times for each preview, am I right?

This is what I would do to visually compare noise in different images: Apply STF to one of the previews, then copy that to histogram transformation tool, and then apply that histogram transformation to the remaining previews - in this way you are applying the same stretch for all 3 previews.

EDIT: I think perhaps it would be interesting to compare regions with stronger signal in these images, just for fun

EDIT2: Another random thought...it does not seem right just to look at background and on that basis decide potentially most effective integration. Taking that approach to the extreme...500 frames with millisecond exposure will generate even cleaner "background", but there will be nearly zero signal from a DSO. That's why my suggestion to compare areas with stronger signal as well

Hey S :-)

That's an interesting point about the presentation/stretch. If I do the same stretch for all of them one is going to be much brighter than the others (because it's exposure was 5 times longer), which I think might make it more difficult to compare noise. Having said that, a non-linear transformation probably isn't the best choice for presenting this either because it could have impacted the comparison.

This isn't background by the way, it's the edge of the brighter region of the nebula; it captures probably the strongest area of signal in the image and where it falls off a bit.