This is mainly a bug fix release for the reported bugs in beta47. In addition it has a significant User Interface performance improvement noticable when you need to process 1000s of images in APP.
2026-10-03 APP 2.0.0-beta47 has been released !
This is a very big release... many code optimizations/rewrites, many parts of APP are much faster and more precise, especially star analysis and registration are much faster ! Big mosaics will go much faster 🙂
And we introduce a new preview filter, which includes the new Adaptive Deep Sky Stretch and a General Levels Stretch, this has been long over due. The old preview filter (the panel on the right side to stretch and preview your data) has not been updated for a couple of years and it is a critical part of any APP session.
Adaptive Deep Sky Stretch or ADSS is a much more intuitive stretch algorithm. It is also color preserving (which is a great new addition in itself ! ) which means that the highlights are no longer bleached, color is maintained from the linear data while stretching. You can simply stretch your data using the sky background level and signal width sliders which work much easier and more intuitive. You no longer need to fiddle with the old complicated sliders with zoom buttons. All the zoom buttons for the sliders are made redundant. And you can enter slider values in the slider value fields yourself. I will make a youtube video in the coming days to explain and fully introduce ADSS. Once the video is ready, it will be highlighted on the forum.
RGB Combine upgrade !. The RGB Combine Tool has been rewritten mostly. The tool is faster and easier to use and most importantly, the Luminance slider to inject a luminance channel or channels into the RGB composite is now working correctly. It no longer bleaches the RGB colors. Combined with the new ADSS preview, you will get much better and easier great composites with great color! I will also explain this in a new youtube video.
Faint comet in rich star field - manual registration mode?
How can I best use APP to stack multiple images of a faint comet that is situated in a rich star field? Is there a manual/override registration mode where a user can choose the first and last images in a time-series, manually place crosshairs on the comet nucleus, then have APP determine x and y pixel drift rates (based on exposure time data in the images) to 'open loop register' the entire time series?
It's relatively easy to automatically register on a comet when it's bright and the star field is sparse. As the comet gets fainter and star field richer, the automated recognition/centroiding task gets difficult, maybe impossible. A manual/open loop registration mode can handle this problem better.
Did you already try the comet registration tool in APP to see if it detects the comet properly? Normally it does, there was some improvements done on detecting nuclei as well, it sometimes will ask to manually select it again if it proves difficult.
@vincent-mod I have used the comet registration tool for all my recent comet images. I am giving APP a difficult problem because I'm imaging a faint comet against a rich star field. Here is one example. The crosshairs are actually not on the comet. The comet is several pixels above the crosshairs.
For that image I was unable to manually coax the crosshairs onto to comet, so I did not use it in the final stack. Images from several minutes later, when the comet had moved farther away from the distracting star, I was able to manually place crosshairs on the comet...but it required manual intervention on the vast majority of images.Â
Here is my most recent image of comet 104P Kowal.
This was a stack of 236 images. Because of the rich star field, I had to manually position the crosshairs on at least 3/4 of the images. The centroiding routine appears to be quite accurate, even on this faint comet, but the requirement for so much manual crosshair positioning is tedious.
Ah I see, that is indeed a bit challenging. Would be great if you could share this data with us, I'll also forward your request to Mabula. If you can, please upload to the server mentioned top right of the forum, in a directory called "tomkrajci-manualRegMode".
Note that I have separated the light frames into the three sessions of the barn door drive.
The barn door drive is not perfect. In the middle of each run tracking performance/image quality is pretty good and pretty consistent. Near the beginning and end of each run fewer images are of acceptable quality. If you want to save time while evaluating registration algorithms, select only a small subset of images from the middle of each of the three runs.
When I processed the images I opened the lights in 'super pixel' mode. I wanted to go deeper with a 2x2 bin, and I think the improvement in image resolution using 1x1 binning is not very large because of the tracking/image quality.
I hope this set of images and calibration frames helps.
This was a stack of 236 images. Because of the rich star field, I had to manually position the crosshairs on at least 3/4 of the images. The centroiding routine appears to be quite accurate, even on this faint comet, but the requirement for so much manual crosshair positioning is tedious.
Looking at the result, it seems APP worked fine allthough it took a bit of manual labour for you. If the comet is weak like this, if the current comet detection has low certainty, it will ask you to manually select the core. If stars are nearby of similar or higher brightness, then the comet detection might fail yes. But since APP is calculation comet speed relative to the stars, it can correct those images as you can see in the final result.
I have added to our issue list to test your data to see if we can improve things further 😉
