satellite and hot pixel track suppression in software

Started 2 months ago | Discussions thread
hha1 Junior Member • Posts: 29
Re: satellite and hot pixel track suppression in software

Alen K wrote:

The walking noise ( due to gaussian noise spikes) is also virtually eliminated by sigma clipping.

I have my doubts about that, especially if you are limiting the clipping so much. Can you provide a comparison of pure accumulate vs. kappa-sigma clipping that demonstrates that? If you don't feel like proving it to an old doubting Thomas like me, that's okay.

This is exactly the point I made with the two images  at the start of this post. The one on which shows the hot pixel trail was with simple accumulation, the other shows the result of accumulation with 3.5 sigma clipping. If one assumes that

1. The 100 measurements for each pixel are gaussian distributed with a few positive outliers (noise spikes) , and

2. the standard deviation can be estimated from 100 numbers per pixel (using what is called in the literature a robust standard deviation),

then 3.5 sigma clipping will clip the brightest 0.1% of the pixels  99.9% of the pixels in the image are untouched. With 2 sigma clipping virtually every pixel will have its brightest, but not is darkest  values clipped. This means that the faint stars get fainter. If you are accumulating only 10 frames, than the standard deviation will be very uncertain, as will be the result of the clipping.

Have you tried the worm error and flexing with your setup?

I don't use a tracker (anymore). My current, highly-portable setup depends on Astrotracer. Random dithering is a natural consequence of how that must be used when creating large stacks (much more work than saner people than I will do). No worm error (no worm gear) and no flexing problems. The camera or lens is mounted directly to a tripod, like this. My other setup uses a Vixen GP-DX Goto mount, so no flexing of that sort even when it is supporting one of my telescopes. Unguided PE is less than 5 arcseconds (when the PPEC is properly trained).

Your highly portable setup looks intriguing. Can you share any results with it to win me over?


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