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.
Sorry for the late reply ! I have been busy lately.
As you asked, the complete dataset is uploaded in the folder ''Fred-OutlierRejection-issue''
I've just tried the median integration but don't see any improvement from average integration !
Yes I've always used LNR and also LNC (tested with 2nd et 4th degree with 3 iterations).
Thank you for you assistance
Fred
Hi Fred @fredmt,
I am testing your data now, trying to improve this 😉 Just a question for now, it is clear that the data has many satellite stripes and I am wondering if you have tried adjusting the outlier rejection with the diffraction protection setting as well? Or did you not touch it?
Mabula
Hi Fred @fredmt,
I have played with your data, and you want the diffraction protection to be set to none ! or very high. With 5, all those satellites will survive easily.
I am still testing and will probably improve this behaviour in the next version 😉
Mabula
Hello everyone. If you switch off the automatic mode in tab 6 under Integration and set median, all satellite tracks are removed.
The only disadvantage is that you have to do without multiband blending and Bayerdrizzle. With Bayerdrizzle the stars would have less color fringing.
If you switch from quality to SNR at weights, you still have a better object signal without having to deal with new color gradients (for example through clouds etc.). The SNR setting follows the brightness of the sky background well. So images with a darker background are weighted higher.
Although it is considered a dangerous weighting option in the tooltip.
Integration Average
Integration Median
Greetings Henry.
Hi @minusman,
Thank you very much for your information and help in this issue, I am working on this issue and I can confrim that with median integration, the satellites are cleanly gone. The downside is that median integration is inferior when it comes to noise reducation in stacking when compared the median integration. I am working at the moment on Local Normalization Rejection 2.0 to solve this while still maitaining good SNR in the integrated result.
I have done extensive testing using Fred's data @fredmt and the there are so many satellites in the data that the unrejected pixelstacks remain biased with some residual outliers. And these residual outliers seem to not be removed due to a normalization issue, like you suggested earlier, so I think that is a very good analysis. My solve would be to correct the pixels in the pixelstacks also for dispersion with Local Normalization Rejection 2.0. The current Local Normalization Rejection only corrects for the sky background. Adding dispersion in the correction might solve this. I will soon know if it works 😉
Mabula
