Author Topic: M1 image issues  (Read 3003 times)

Offline dcbrown73

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M1 image issues
« on: 2014 December 28 15:50:35 »
Hi,

I took (15) three minute images of M1 in Ha, SII, and OIII  using a remote observatory.  I then stacked them and received three master images, but either the images is terrible or I haven't a clue what I'm doing with these types of images.    I have worked with Ha images before as I have LRGB and an Ha filter for my CCD.  I have never seen images like these before and I was hoping someone could look at them and tell me if the issue is with me or the images themselves.    Also, when I try to stretch them, it's like nothing I've seen before.  The image basically goes straight to white very quickly.  They also seem like that have tons of black pixels in them.  I've never seen anything like it.

You can find the three stacked master images here.  (Google drive share)

Thanks,
Dave

Offline msmythers

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Re: M1 image issues
« Reply #1 on: 2014 December 28 17:03:55 »
Dave,

I'm not a CCD guy at all but I'm willing to put my foot in my mouth. First looking at how noisy your images are I would guess you need more exposure time,maybe. Second your stacked images have a high number of hot and dark pixels. First I wonder if your calibration was correct. Another area for this issue is during the Integration(stacking) process did you use the correct pixel rejection algorithm.

The image going to white after stretching sounds like STF is still active and needs to be reset.

I think it would be helpful to know what remote site was used so others can comment. They might have insight on how to handle data from the site and if there are steps you need to know about.

Here is a very basic and quick processing of your image.



Mike



Offline dcbrown73

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Re: M1 image issues
« Reply #2 on: 2014 December 29 07:28:54 »
Thanks Mike.  I came up with something similar processing it.  Notice all the artifacts of all different colors in the image?  I'm not sure how or where those came from.  I've seen stuff like that before, just not that bad.

btw, I ensured that I disabled the STF when I tried to use the Histogram tool.

The images were taken at New Mexico Skies.  Specifically, iTelescope.net.  The T5 telescope.

Offline MikeOates

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Re: M1 image issues
« Reply #3 on: 2015 January 05 02:22:42 »
Dave,

A quick edit here. I have no idea why I read 3 subs per filter from!!. But having said that I hope the other tips are of some use to you.

As you only used three subs from each filter, your not going to get a good result. I have found that although three is the minimum number of subs you can integrate in PI there is no or very little rejection taking place. There is a slight improvement with 4 subs, but do 5 and there is suddenly a big improvement. So I suggest using 5 subs as a minimum (but more the better). If time on the telescope is restricted, then I suspect you may get a better result taking more subs of a shorter exposure time. So for example instead of taking 3 x 5min subs, take 5 x 3min subs.

Most of the bright colours in your image are probably from hot/warm pixels that are not being rejected due to the small number of subs.

I also think that you may have applied too much colour saturation which is exaggerating the problem.

You can always take extra subs of the same object on another night and then integrate them altogether, so your data/time has not been wasted.

You can also make a pixel rejection map from the telescopes dark frames,  then use defect map that will remove all the hot/warm pixels which will improve the result from your existing data. This page will help with the process: http://pixinsight.com/forum/index.php?topic=4218.0

Mike
« Last Edit: 2015 January 05 06:04:27 by MikeOates »

Offline oldwexi

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Re: M1 image issues
« Reply #4 on: 2015 January 05 05:32:47 »
Hi Dave!
The data are o.k. There are several processing changes necessary.
Major issue, You integrated the 15 Images per channel without(!!!) Pixel Rejection.
So redo the Integration per channel using Pixel rejection Windsorized Sigma clipping.
This removes all the hot Pixels and hopefully the dark Pixels too.

These Images are not very noisy but you have overdone the "softerning/denoising" this gets this blotches.
Use MMT noise reduction with an inverted mask to carefully reduce noise in Background.
More Images with more exposure time would increase Quality also.

Find a try with your data here:
https://www.dropbox.com/s/uodxldjn4c8wz08/rgb3_Preview01.jpg?dl=0

Gerald
« Last Edit: 2015 January 05 06:07:09 by oldwexi »