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by incrudible
859 days ago
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Does it lead to better results though? For the system, the best representation would be one that it learned - which is the latent representation, 4 channels in this case. Would it learn a "better" representation when fed with HSL instead of RGB? If so, what's the intuition? RGB somewhat resembles human vision, whereas HSL exists for interactive editing, and YCbCr exists for compression. If anything, I would expect YCbCr to outperform. |
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HSV closer resembles physical properties, for most natural things. Hue and saturation variations are usually meaningful variations in the actual material. Brightness variations often end up being mostly about lighting, rather than the material. It can be surprisingly effective for simple segmentation [1], which is why it's usually the first one implemented in computer vision classes.
Our eyes have RGB sensors, but I would claim I perceive the colors in my surroundings in something like HSV (although, that could very well be from the way I learned colors). And, I think this makes sense: if you're looking for something, you want a color perception that's not overly sensitive to lighting conditions. RGB is directly related.
[1] https://medium.com/neurosapiens/segmentation-and-classificat...