June 24 2026 APP 2.0.0-beta46 has been released !
Improved internal memory configuration (lower ! memory usage), fixed beta45 startup issue, fixed Set Save Directory & 2-panel mosaics.
May 27 2026 APP 2.0.0-beta45 has been released !
Fully Multi-Threaded LNC, many improvements for the registration engine, platform upgrade, and further tuning of internal memory consumption and memory release back to OS.
Apr 14 2026: Google Pay, Apple Pay & WeChat Pay added as payment options
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.
I'm curious, is there an official formula published for how the Quality Score is calculated, similar to the "acceptance criteria" often used in PI? Â I assume it includes FHWM, Star Count, Eccentricity, PSF in the Star Analysis phase, but is there any weighting for each of those? Â Are there any others, like perhaps contrast detection to identify subs that might have been taken with dew on the mirror/objective? Â My apologies if I've missed this documented somewhere.
Also, I know that the calculated quality score changes with the Registration and Normalization phases. Â The general way that I use this score is to sort my Star Analysis results, exclude the poor-quality outliers, then Register, sort on Quality again and repeat, then Normalize, sort on Quality again and repeat (though I often don't have any to throw away at this stage).
I tend to vacillate on what my acceptance threshold is (for only the Star Analysis phase). Â I would normally shoot for no less than 1 standard deviation lower than the mean... but APP doesn't calculate S.D. Â If I'm quick and lazy, I'll de-select the bottom third of the quality scores for each filter. Â If I'm really being picky but still lazy I'll kill the bottom half, but that's throwing away a lot of data and my pickiness usually doesn't produce a noticeably better image. Â Much of the time I will just drop the obvious outliers.
It would be awesome if the Star Analysis tab allowed me to define my acceptance criteria, then auto-select only those subs that meet it after Star Analysis completes. Â Choose .5, 1 or 2 Standard Deviations from a dropdown menu and Star Analysis would select only the subs that meet that threshold. Â (I'm not sure I'd do the same for Registration or Normalization, as it may result in a more data loss than needed, but it'd be interesting to try it).
Hi @mountainair,
The quality score formula changes at each procesing step in APP as you have epxerienced, collecting more and more analytical results. The final formula after 5) Normalize combines all the reported metrics, FWHM size and shape (eccentricity), star count, noise. But there are other methrics like background and dispersion and SNR. You can simply make graphs of these metrics, sort on them and then reject clear outliers. The actual formula will be release in the manual with 2.0 stable. And please know that we will add more options in this regard. Currently the quality score is our fixed formula, we will make it possible to use many different formula going forward.
Finally, in our experience, throwing away so much data like you indicate is usually counter productive in terms of getting good signal to noise ratios in the final result unless you suffer from many frame with bad stars due to guiding issues with your setup, is this the case?
Please be carefull and only throw away clear outliers in the graphs, and you will be fine and get the most out of your data 😉
Mabula