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,
my question is: which is the best de-Bayering algorithm for astrometry and/or photometry when using the images from a one-shot color camera with a large FOV (short focal length) of several degrees?
Did somebody here already use the „Adaptive Airy Disc“ (AAD) algorithm for that purpose? Or would another de-bayer algorithm give better results?
Probably I have to explain here, what the reason for this question is: currently I am doing an experiment using a one-shot CMOS color camera (with Sony IMX571 chip, APS-C format, back-illuminated) with 3.76 micron pixels on the 135mm Samyang Lens. This gives about 6“/pixel (without binning). I want to find out which astrometric/photometric precision can be obtained with this equipment.
My first experience is that residuals (against ATLAS2 catalog) over this large FOV are in the range of 0.5 to 2.5 arcsec. All over! The photometric precision was a bit below 0.1 mag when restricting comp stars to 15 arcmin neighborhood. So far not too bad with such equipment (and without the de-bayer algorithm of APP).
Does anyone here have some experience with de-bayering and could give advice how best practice is for the mentioned purposes (and the above equipment)?
Best regards,
Hipoh
Hi,
my question is: which is the best de-Bayering algorithm for astrometry and/or photometry when using the images from a one-shot color camera with a large FOV (short focal length) of several degrees?
Did somebody here already use the „Adaptive Airy Disc“ (AAD) algorithm for that purpose? Or would another de-bayer algorithm give better results?
Probably I have to explain here, what the reason for this question is: currently I am doing an experiment using a one-shot CMOS color camera (with Sony IMX571 chip, APS-C format, back-illuminated) with 3.76 micron pixels on the 135mm Samyang Lens. This gives about 6“/pixel (without binning). I want to find out which astrometric/photometric precision can be obtained with this equipment.
My first experience is that residuals (against ATLAS2 catalog) over this large FOV are in the range of 0.5 to 2.5 arcsec. All over! The photometric precision was a bit below 0.1 mag when restricting comp stars to 15 arcmin neighborhood. So far not too bad with such equipment (and without the de-bayer algorithm of APP).
Does anyone here have some experience with de-bayering and could give advice how best practice is for the mentioned purposes (and the above equipment)?
Best regards,
Hipoh
Hi @hipoh,
Thank you very much for your interesting question.
I would suggest to you that you do try Adaptive Airy Disc, it should work well. But for best precision, do not demosaic/debayer at all, but rather use Bayer/X-Trans Drizzle, you can set this in 6) Integrate at the bottom 😉
Use Bayer/X-Trans drizzle and set the drizzle droplets to 2 pixels. That should give similar results as demosaicing/debayering in terms of resolution. If you set the droplets lower, you will gain resolution, but will also have more noise.
Let me know if this helps 😉
Mabula
Thanks for your valuable suggestions! I will try both and will report here about the results.
CS! hipoh
