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.
A plane trail once snuck though in my APP integration result. Since that happened I started blinking my subs using other software before processing in APP. But I have so many subs for my current project that blink can't handle the volume. So, I'm wondering which metric that APP generates will best help me eliminate any subs with plane or sat trails.
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@safinsd I am not sure if there is a metric that you can check. However, in tab 6 you should set the "integrate" drop down to either "median" or "average", enable "local normalization rejection" and choose either "winsorized rejection" or "adaptive rejection". In both cases the choice depends on the amount of frames you have. See the mouse hover tool tips for more info.
Once that's all set, you'll need to play with the "kappa low" and "kappa high" values. The lower either is set, the more data gets rejected. Note, as is explained in the mouse hover tool tips, that setting those values lower will increasingly reject good data as well so make sure not to set them too low. You'll need to find a balance between rejecting the trail and rejecting signal that you actually want to appear in the integration result.
What is kappa - i.e. what levels of probability does it correspond to (e.g. sigma score of 3 corresponds to 99%). For a very low number of frames (e.g. 2) and with two types of outliers - plane trails (light) and trees (dark) what would be optimum values of kappa? Plane trails are VERY bright and tree branches are VERY dark so they should be easy to detect.
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Thanks much for your very helpful reply. I selected median-average and local normalization rejection-adaptive rejection. Looking forward to the result.
Thanks for the link where Mabula said "Kappa is the number of times the scale/dispersion factor is applied for rejection. Scale/dispersion is usually the standard deviaton." I knew that but I was hoping for a translation into probability because "number of times" has no meaning to me. Is kappa like a z score?
@ddnum, kappa is simply a number which you set to control how many times the scale/dispersion is used to determine which pixels should be rejected or not.
For example a high kappa of 3, means that all pixels above
central value + 3*scale
will be rejected in all pixelstacks of your integration.
If the pixelstacks would have a nornal/gaussian distribution, then the following applies: https://en.wikipedia.org/wiki/68%E2%80%9395%E2%80%9399.7_rule
Unfortunately, the pixelstacks only approach a gaussian, so the probability is slightly different and lower as a consequence...
If APP's automatic rejection still leaves outliers like airplanes, you want to disable automatic integration and control the rejection settings yourself like Wouter @wvreeven indicates 😉
The settings that APP used in the automatic integration are stored in the FITS header of the integration, so you lower the kappa high and low from those values until all is to your satisfaction.
Mabula
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