Why would image processing use LUV instead of RGB?
Asked 9/1/2015
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Some image-processing applications extract or compare information in the LUV color space rather than directly in RGB. What makes LUV preferable in some cases, and when would it be used instead of RGB?
Originally by Photography Stack Exchange contributor. Source · Licensed CC BY-SA 4.0
Photography Stack Exchange contributor
10y ago
2 Answers
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I found this explanation at imagemagick but am not an expert on color spaces myself.
Perceptual Colorspaces
The colorspaces 'Lab' and 'Luv' are designed, such that they fully separate the greyscale intensity from the color components of an image. Unlike 'RGB' and 'sRGB' colorspaces. this makes the colorspace a lot easier to process and modify in general, once you get the hang of it.
More specifically 'Luv' was designed to be 'perceptually linear'. That is that a a small change in color in one part of the colorspace looks to be about the same, as a similar change in another part of the colorspace. This make LUV colorspace much better suited for image difference comparisions.
Originally by user35348. Source · Licensed CC BY-SA 4.0
user35348
10y ago
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LUV is sometimes preferred because it separates brightness (luminance) from color information more cleanly than RGB. In RGB, intensity and color are mixed together, which can make some kinds of processing harder.
A key reason to use LUV is that it was designed to be more perceptually uniform (or “perceptually linear”) than RGB. That means a given numerical change in color is intended to correspond more closely to a similar visible change across the space. Because of that, LUV can be better for tasks like:
- comparing image differences
- measuring color similarity
- processing color independently from brightness
So, RGB is common for capture, display, and storage, but LUV can be more useful for analysis and certain image-processing operations where human-perceived color differences matter.
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