Stackistry - a lucky imaging/image stacking tool

[GreatAttractor]

I present an early version of my lucky imaging/image stacking tool. Usage description in the README file. Source code and a 64-bit Windows binary can be downloaded from:

https://github.com/GreatAttractor/stackistry/releases

(to launch, use stackistry.bat).

In case of questions and problems, post here or send me an e-mail (address in the README). If Stackistry produces a poor-quality stack, it would be very helpful for me to be able to download the problematic raw video.

[michael.h.f.wilkinson]

Just downloaded it. Will give it a spin shortly. Thanks for all the good work

[NickK]

One things have settled down here (new job) I'll be interested in seeing how this works on my new ODroid C2 (quad core arm) for solar work.

 

[GreatAttractor]

New version: 0.0.2

Download: https://github.com/GreatAttractor/stackistry/releases

Bug fixes:

- Fix errors when stacking a series of TIFFs
- Use all fragments if criterion is "number of the best" and the threshold is more than active images count

[GreatAttractor]

New version: 0.0.3
Download: https://github.com/GreatAttractor/stackistry/releases

New features:
- Demosaicing of raw color images

Bug fixes:
- Error on opening SER videos recorded by Genika software
- Incorrect RGB channel order when saving a BMP

You can find more on demosaicing (“debayering”) in the README.

[GreatAttractor]

New version: 0.1.0
Download: https://github.com/GreatAttractor/stackistry/releases

New features:
- Multilingual user interface support
- Polish language version

 

If someone would like to create another translation, let me know.

[kamayok3]

It is a great software. Thanks for the good work!

Edited June 7, 2016 by kamayok3

[GreatAttractor]

New version: 0.1.1
Download: https://github.com/GreatAttractor/stackistry/releases

New features:

• Support for Y8/Y800 AVI files

Enhancements:

• User-configurable brightness threshold for automatic placement of reference points

Until now the local brightness threshold to place the reference points was hard-coded to 33% (relative to the brightest pixels in the image). It was fine for planets and the Sun, but not necessarily for the Moon. Example of various threshold settings (from the left: 10%, 33%, 70%):

 

(Of course you can always just use manual placement, if automatic doesn't do the job).

[GuLinux]

I just had a quick try.

I'll be able to write a full review in a few days.. need to get the hang of it first

In the meantime, thanks, and keep up the good work!

[GreatAttractor]

Have fun!

Keep it mind that at the moment automatic processing is best tuned for Hα surface imagery (i.e. what I do most often) and high-resolution solar white light. For prominences with an overexposed (white) disk and planets, manual placement of ref. points is recommended.