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Mar 28 2026 APP 2.0.0-beta40 will be released in 7 days.

It did take a long time to have the work finished on this and it  will have a major performance boost of 30-50% over 2.0.0-beta39 from calibration to integration. We extensively optimized many critical parts of APP. All has been tested to guarantee correct optimizations. Drizzle and image resampling is much faster for instance, those modules have been completely rewritten. Much less memory usage. LNC 2.0 will be released which works much better and faster than LNC in it's current state. And more, all will be added to the release notes in the coming weeks...

Update on the 2.0.0 release & the full manual

We are getting close to the 2.0.0 stable release and the full manual. The manual will soon become available on the website and also in PDF format. Both versions will be identical and once released, will start to follow the APP release cycle and thus will stay up-to-date to the latest APP version.

Once 2.0.0 is released, the price for APP will increase. Owner's license holders will not need to pay an upgrade fee to use 2.0.0, neither do Renter's license holders.

 

Unknown error message

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(@jehoener)
Red Giant
Joined: 7 years ago
Posts: 28
Topic starter  

Hello.  What does this error message mean?

I ran my color channel integrations through DeNoise AI before combining, and I receive this message when I attempt to open some of them, but not all.  I've renamed them but the problem persists.   Thanks.

error message on opening image after DeNoise AI

 


This topic was modified 5 years ago by Joseph Hoener

   
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(@wvreeven)
Quasar
Joined: 8 years ago
Posts: 2134
 

@jehoener That is difficult to say without more details. What OS are you on? What version of APP? What file type (FITS, TIFF, something else) are you trying to load? Does the error happen when you do not run the files through DeNoise AI? What kind of files are you trying to load (LRGB, Ha, OIII, etc)?

Wouter



   
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(@jehoener)
Red Giant
Joined: 7 years ago
Posts: 28
Topic starter  

@wvreeven  Wouter: 

Windows 10;  APP 1.082; .tiff file; trying to load Ha, L, R, G and B integrations.  I don't get the error when loading the files that have been run through DeNoise AI.  I have instructed DeNoise AI to save the files in the same format as the original images.  Incidentally, I cannot open the DeNoised files in CCDStack, either, so DeNoise AI has apparently modified the files in some unknown way.

 



   
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(@wvreeven)
Quasar
Joined: 8 years ago
Posts: 2134
 

@jehoener I am not familiar with DeNoise AI but it sounds like you want to minimize noise before combining the integrated panels which in general is not a good idea. I’d advise you to first combine and process the panels as much as possible in APP before attempting denoising and other processes. 

On top of that, it looks indeed like the TIFF files get modified such that APP (and apparently other software) cannot handle them. That would also indicate that it would be better to do the denoising as late as possible. 



   
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(@mabula-admin)
Universe Admin
Joined: 9 years ago
Posts: 5056
 
Posted by: @jehoener

@wvreeven  Wouter: 

Windows 10;  APP 1.082; .tiff file; trying to load Ha, L, R, G and B integrations.  I don't get the error when loading the files that have been run through DeNoise AI.  I have instructed DeNoise AI to save the files in the same format as the original images.  Incidentally, I cannot open the DeNoised files in CCDStack, either, so DeNoise AI has apparently modified the files in some unknown way.

 

Dear Joseph @jehoener,

Could you upload a couple of those problematic Tiff files to our server, so I can check exactly what is happening 😉 Maybe I can find a way to make them work.

https://upload.astropixelprocessor.com/

username: upload4

password: upload4

I do agree with Wouter @wvreeven, I would recommend to NOT perform noise reduction when you still need to combine the linear images. Noise reduction will alter the statistics of the data considerably and since noise reduction algorithms behave rather inconsistent between different images (especially different Field of View), the data normalization will probably suffer as a consequence... so I don't really expect the results will be better in the end as well.

Mabula



   
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