Author Topic: Debayering using neural network upscaling  (Read 907 times)

LSeww

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Debayering using neural network upscaling
« on: April 14, 2021, 08:02:13 PM »
I'm trying to use Topaz Video Enhance AI to upscale red and blue channels in order to create a better RGB video from RAW.
From one RAW file you can create R and B channels with half resolution, and then upscale them with AI into full resolution.
As for the G channel I just use averaging. It works quite nicely (no aliasing on EOS M and almost no color noise) however I ran into an issue: although I can split RAW into R, B and G fast enough, I can't do averaging for missing G pixels as fast enough with my tools. There must be some kind of RAW editor to do that, but I found mostly python and C code which is less desirable. Any suggestions?

tit_toinou

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Re: Debayering using neural network upscaling
« Reply #1 on: September 01, 2021, 07:45:07 AM »
It could be a great idea to directly train neural networks to upscale from raw data. It could lead to better performance than normal upscaling
5DIII