Sunday, October 13, 2013

New project: pyAstroStack

It has been bothering me that there are no free stacking software for astrophotographers for Linux. I've heard PixInsight is awesome and I have no doubt, but it costs money. I wonder why no one has ever made a free (as in freedom) alternative. Maybe because there are decent free (as in free beer) programs such as DSS, Regim or IRIS (which I compared here).

I decided to try and code one myself. I basically understand a lot of the mathematics involved. I've studied programming a bit alongside physics and mathematics so I thought I might have the skills... Still there has been some problems where I least expected them. For example making an affine transform for a data matrix was surprisingly difficult.

So now I announce:

pyAstroStack

An open source stacking software for astronomical images

For now the program is extremely limited. It works from command line and is configured by editing the source code. It also does stacking only by average value, doesn't calibrate images with dark, flat and bias, saves result only in three fits (one for each colour channel)... But it works for my test data! That's when I thought I'd make this public.

My test data was the best astrophoto I've taken. Not much as you can see, but nevertheless it is my best. Here's the first successful result of my own code.

Andromeda, stacked with pyAstroStack and postprocessed with ImageMagick and Darktable
Stacking was done in pyAstroStack and open source software was used also for the postprocessing. First I tried Iris for setting colour balance on the FITS and saving it as TIFF and it did a lot better job than I could in Darktable. My goal was to have everything done on open source software so that's why no Iris is used on this image.

And here's the same stacked with Iris http://www.flickr.com/photos/96700120@N06/10002768985/in/set-72157634344389164

The code can be seen in Bitbucket. It's licensed under GPLv3. I hope this'll go somewhere and that I have time and resources to make it easier to use and install. If you read this far, I assume you are somewhat interested in the project. Awesome. If you have any ideas on how to make the registering faster or reduce the number of required Python libraries, I'm all ears.

Feel free to add enhancement or proposal ideas on issue tracker in Bitbucket.