2026-10-09 APP 2.0.0-beta48 has been released !
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.
Debayering OSC images introduces noise because it uses interpolation instead of the true value. This noise is fixed if the image is not moved in the frame so stacking won't average it out. My questions are specific to the APP debayering algorithms (but feel free to chip in with others).
Will dithering reduce this noise? If so, what is the optimum number of pixels to dither each frame by? Presumably we should dither by an odd number of pixels right? Do these answers change if we don't use the Adaptive Airy Disk option?
Hi @ddnum,
Thank you for your excellent question 😉
For sure, dithering will reduce the debayering artefacts very nicely. As it would all other noise factors as well.
Debayering means demosaicing a Bayer Color Filter Array (CFA) pattern of 2x2 pixels (eg. RGGB), so we can simply assume that we need to get rid of a 2x2 pattern. Now from sampling theorem you would greatly reduce the 2x2 pattern by sampling this 2x. So that would mean to dither in a range of 4 pixels to get quickly rid of the demosaicing artefacts 😉
Since there are, no doubt, other noise patterns on your sensor, there is not an optimale dither range. Simply put, the bigger dither step that you can take, the better. Overall noise will drop faster with integrating frames with bigger dither steps until you reach the theoretical limit for noise reduction.
In my experience, it is very good and normal to dither with dither steps of 10-20 pixels on most sensors. If you would only dither a couple of pixels, noise reduction will not be that optimal 😉
This answer will not change if you use another algortihm than Adaptive Airy Disc.
Dithering odd or even amount of pixels does not matter, the dither algorithm randomizes the size and direction of the dither steps.
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