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.
Hello,
First of all, THANK YOU so much for this new version 1.077. The pleasure of processing our images is all the more pleasant.
I am validating a procedure to obtain the best possible treatment for color images produced using a camera whose Bayer pattern is RGGB.
After having realized the "split channels" of my color images and in order to obtain the best "realize / ideal noise reduction ratio (ratNR)", I used the zero tab "Bayer CFA" where I used the following parameters and continued processing until integration:
* RGGB Pattern
* Adaptive Airy Disc Algorithm
* Force Bayer CFA
For stacking, I got the best results with "bayer drizzle 1.0" and "droplet size 2.59".
Thus, I obtained for each filter (R, G, B) three channels each having their own "ratNR".
For the combine RGB, I did some tests by considering all the channels R-c1, R-c2, R-c3, G-c1, G-c2, G-c3, B-c1, B-c2, B-c3 or by not considering only one channel per filter is the one with the best "ratNR" (eg, R-c2, G-c2, B-c1).
At this point, I wonder what is the best or the best strategies to test to take advantage as much as possible of the captures of our color images.
Is there a tutorial on this?
Tanks in advance and Have a nice day,
Max
