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.
Hi.
I've been following this famous workflow since the beginning: https://www.astropixelprocessor.com/community/tutorials-workflows/combining-r-g-b-with-ha-oiii-data-using-an-optolong-l-enhance-filter/
to have a good, real stars color in the final image.
But since single R,G,B channel is split by 50% within LPro and Extreme filter in equal weight (R: 50% extract-Ha, 50% R-LPro, G and B: 50% extract-O3, 50% G-B LPro), I wonder if star colors are really the most accurate as real as possible...
 LPro (split in single R,G,B channels) + L-eXtreme (split in extract Ha and O3) combined in RGBHOO
just L-eXtreme (split in extract Ha and O3) combined in HOO1
For my taste, there is an improvement in the first image, but not as noticeable and clear as I would expect to see...
What is a good workflow to obtain the most accurate and real star color?
Thanks
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Hi Ippiu,
Yes when dealing with narrowband data and mixing that with RGB (which usually is of lower intensity), it can be quite challenging to get proper star colors. This is why many in other packages remove the RGB stars and add those back into the narrowband data. This is something that will be possible in a future version of APP as well and the star removal feature is a way towards that goal. In the mean time, I think more data on RGB will help and reducing the amount of narrowband added to the mix. It's a balance.
@vincent-mod
Very clear...
Thanks...
With LPro filter, oher than adding true star color to narrowband data, what else can I add with LPro filter to final image obtained only with narrowband data?
I made some tests, and honestly I can't see much difference from LPro+ L-eXtreme image - compared with just L-eXtreme image (both obtained with RGB combine tool)...
So, to be honest, is it worth to double the imaging time for a slight improvement?
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Well, good question, maybe longer exposed RGB data is better then. Did you try to lower the amount of narrow band data in the resulting image?
Did you try to lower the amount of narrow band data in the resulting image?
Not yet...On the contrary, I'm doing test on only few RGB data (just 4 hours) compared to 10 hours of narrowband data...
So perhaps you are right: I should add more RGB data, at least the same as narrowband, and then re-do the test...
