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.
Hi,
In my stack headers I can see info about noise reduction.
Is APP adding NR?
If yes, where to disable it?
No it doesn't
I think that is the stacking calculation of the noise. But I could be wrong. It does that when it saves the stacked final file.
/Stefan
Hi @pkolano, @digitaliz-se,
Stefan is completely right here 😉
The noise reduction mentioned in the Fits headers of your stacks are the general noise reductions achieved due to stacking images. So there is no other noise algorithm active somewhere. The whole reason of stacking images is to reduce the noise and this is what is reported.
For example, if you stack 100 images, you can theoretically achieve a noise reduction in the stacked result which is the square root of number of images, so square root of 100 = 10. If the stack reports a noise reduction of a factor of 10, then the stack is theoretically perfect/optimal 😉. No other stack application or tool would be able to improve over that, since this is how this works mathematically. So using these noise reducation factors, you are able to see if APP performs well or not on your data. If you don't come close to the perfect result, you either use too little data, have bad calibration frames, use too little dithering between images, or the data is of low quality in general creating issues maybe.
Hope this explains it?
Mabula
