need help with this image (M8 + M20)

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cknjj
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Joined: Sun Mar 04, 2012 5:50 pm

need help with this image (M8 + M20)

Post by cknjj »

Hi all,

manage to capture a series of images with M8 & M20.
had about 20 over lights. But after stacking there's
always a bright patch on the upper right corner.

This sample pic is jus a single picture without any stacking.

Can anyone advice how to remove the uper right corner
patches without darkening the nebulosity for M20 & M8?

Thanks in advance
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yltansg
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Re: need help with this image (M8 + M20)

Post by yltansg »

You may want to investigate the source of the bright light and tackle that instead.
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cataclysm
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Re: need help with this image (M8 + M20)

Post by cataclysm »

Alfred is right, looks like gradient from light pollution, there must be a stray light source creeping into your objective. PS can help to lessen the effect or this program from Russel Crowman might do the trick: http://www.rc-astro.com/resources/Gradi ... wnload.php .
But the best solution is to isolate the problematic light source. :P
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rcj
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Re: need help with this image (M8 + M20)

Post by rcj »

Hi cknjj,

Could have a few reasons for the uneven illumination:

1) Vignetting due to non-orthogonal imaging train (although it would have to be quite severe in this case since it is highly assymetric (off center).

2) Local light source disturbance. You need to use a longer dew shield, or shoot at a different place within that site, or away from direct light sources.

Removal of gradients, so far as catalysm has mentioned, Russell Croman's application (GradientXterminator) is the easiest to use, though not necessarily 100% effective. It is also not free. You could try IRIS, but there is a learning curve to it. Otherwise if you have the raw frame, I could help to investigate and remove it as much as possible (email to remuscj at yahoo dot com).

Try to take flat frames for that particular mode of setup when you used to take this image, and dividing it with the raw images. If the result appears correct with more uniform background, then the problem is attributed to (1).

Hope this helps! Have fun learning too!
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