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What is the best color space when working with infer LUT?


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is there any issue with inferring a LUT in a full ROMM RGB environment?

It looked very off (just overall bad quality) when I did so, but when I converted everything to sRGB everything looked perfect.

What are your experiences with this? is there a recommended color space or did I just do something wrong somewhere?

 

(I had original files and AFP files so I knew how it's supposed to look)

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Below my 2 cents. I'm not an expert in this area, my knowledge is based on Wikipedia, some tutorial videos, and own experiments in Photo.

 

Do you use RGB/8 or RGB/16?

When using wide gamunt color profiles with RGB/8, lightness values get even more compressed, as the 8-bit values must cover a wider gamunt.

here a RGB histogram: every values is used 4096 times, evenly distributed.

image.png.cf022107f97f5260053abf6edc54ecb5.png

Same file converted from sRGB to ROMMRGB:

the "middle" tones must stem ~7.500 pixels, and the lower 1/4 and higher 1/8 is not populated well (those levels are rarely used in the file, because they belong to colors outside sRGB, which are not in the file)

image.png.fceb0c877c6989ce823aa015a6570eaa.png

When using the same LUT (e.g. 17x17x17), the quality of the interpolation is a bit less in ROMMRGB vs. sRGB.

Besides that, LUTs are the default solution and specifically intended to convert between color profiles. But this does not play a big role for Affinity, because it has build-in routines to convert (probably not based on LUTs).

LUTs are a good way to apply adjustments fast, using interpolation. It is by design and unavoidably a lossless method, except in constructed edge cases. Focus is more on speed, and less on accuracy.

When using LUTs combined with multiple color profiles, you should organize them seperate per color profile. Reusing a LUT, inferred from images in sRGB, and applied to a different color profile may create "creative" results, but no good results.

Even the same adjustment will lead to different results when applied to images using different color profiles.

But the visible difference should not be too extreme.

 

 

 

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