2026-10-09 APP 2.0.0-beta48 has been released !
This is mainly a bug fix release for the reported bugs in beta47. In addition it has a significant User Interface performance improvement noticable when you need to process 1000s of images in APP.
2026-10-03 APP 2.0.0-beta47 has been released !
This is a very big release... many code optimizations/rewrites, many parts of APP are much faster and more precise, especially star analysis and registration are much faster ! Big mosaics will go much faster 🙂
And we introduce a new preview filter, which includes the new Adaptive Deep Sky Stretch and a General Levels Stretch, this has been long over due. The old preview filter (the panel on the right side to stretch and preview your data) has not been updated for a couple of years and it is a critical part of any APP session.
Adaptive Deep Sky Stretch or ADSS is a much more intuitive stretch algorithm. It is also color preserving (which is a great new addition in itself ! ) which means that the highlights are no longer bleached, color is maintained from the linear data while stretching. You can simply stretch your data using the sky background level and signal width sliders which work much easier and more intuitive. You no longer need to fiddle with the old complicated sliders with zoom buttons. All the zoom buttons for the sliders are made redundant. And you can enter slider values in the slider value fields yourself. I will make a youtube video in the coming days to explain and fully introduce ADSS. Once the video is ready, it will be highlighted on the forum.
RGB Combine upgrade !. The RGB Combine Tool has been rewritten mostly. The tool is faster and easier to use and most importantly, the Luminance slider to inject a luminance channel or channels into the RGB composite is now working correctly. It no longer bleaches the RGB colors. Combined with the new ADSS preview, you will get much better and easier great composites with great color! I will also explain this in a new youtube video.
How can I interpret these results?
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@stephanhamel22 The number of stars and the minimum and maximum FWHM are mentioned. Based on that, APP calculates a quality score based on internal algorithms and that score is displayed as well. The rest are other ways to display the same information.
- Thank you for this. What is the perfect score?  Is this decent score? There are no published references to compare with?
@stephanhamel22 It is very difficult, if not impossible, to provide a perfect score. It depends on the optical quality of the telescope, the size of the camera pixels, the seeing, guiding, and many other factors.
There are several online tools that provide means to calculate the theoretical plate scale in pixels for your telescope and camera. You can compare that value with the FWHM value to see how well you are doing.
The quality score not only depends on FWHM but also on SNR so it is even more difficult to judge whether a score of about 500 is good or not. But APP allows for using only part of the lights for the stack and which ones are used depends on the scores of the frames.
I have to admit this is still the most frustrating/mysterious part of APP for me next to the Correct Vignetting feature (only matched by the DELIGHT i experienced when I realised that I didn't need to slavishly click through all the steps 1-6 saving along the way and that I could just click Integrate and I would have amazing results - literally changed my love for the hobby that day!)
I don't have a suggestion other than somewhere something needs to pop up explaining what the score means and, ideally, allow the user to "blink" the frames (aligned and in order) to determine which ones to keep/reject (in addition to the very cool, but not always the smartest "auto" setting).
Just to be clear - the above sounds like a complaint, it's not - but having asked this question myself, I am confident that I am not the only one confused by how to interpret and action the results of those columns.
To add to what Wouter said; the scores are relative to the each other basically. So you can't really use them to compare different datasets (unless processed together) in that way. But you can for instance take the best scoring frames per dataset and combine them with others, so at least you know you'll have the best data per set.
