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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.

Null Pointer Error: Encountered Error in Module LNCRejectionWorker - 1.61

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(@rowland-f-archer-jr)
Neutron Star
Joined: 9 years ago
Posts: 89
Topic starter  

Hi Mabula - I am doing a rather large (878 light frames) integration with multi-channel and multi-session processing, 1st order LNC, 3 iterations, no drizzle, LN Winsor Clip outlier rejection.  It halted after 87% completion with the attached error message.  I found one frame, which was -not- checked, but showed a status of ...NORM FAILED so I removed that from the list and will run again.  I'll update this if removing that frame (which was heavily obscured by clouds) fixes the error.

I wanted to post this in case there is any other information I can provide to help before I shut down this APP session.

Thanks,

Rowland

LNC Error APP 1.61


   
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(@mabula-admin)
Universe Admin
Joined: 10 years ago
Posts: 5468
 

Hi Rowland @rowland-f-archer-jr,

So I assume, that removing that single frame with clouds didn't remove the error?

A frame that wasn't normalised, should not be in the integration, APP autoamtically excludes it.

I need to have a look at the LN clipping algorithm 😉 In some cases, you can see a problem in the rejection output map as well.

Mabula

 



   
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(@rowland-f-archer-jr)
Neutron Star
Joined: 9 years ago
Posts: 89
Topic starter  

Yes, removing it did not prevent the problem.  Removing the problem frame and switching to Winsor Clip instead of LN Winsor Clip worked OK.

 

Thanks,

Rowland



   
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(@mabula-admin)
Universe Admin
Joined: 10 years ago
Posts: 5468
 
Posted by: Rowland F Archer Jr

Yes, removing it did not prevent the problem.  Removing the problem frame and switching to Winsor Clip instead of LN Winsor Clip worked OK.

 

Thanks,

Rowland

Thank you Rowland @rowland-f-archer-jr,

That is what I thought, the error is in the LN rejection algortihm, I will attend to this problem in the coming days.

Mabula



   
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(@jamesmrobins)
White Dwarf
Joined: 8 years ago
Posts: 10
 

Getting a similar error on v1.074.1 running on OSX when performing LNC on a mosaic. All frames normalized.

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