This reminds of Poincaré's remark that all geometries are wrong, they are just useful abstractions of space. The different color spaces all have some features t

This reminds of Poincaré's remark that all geometries are wrong, they are just useful abstractions of space. The different color spaces all have some features they are good at with their own algebra. So, RGB is close to how screen works, but is very un-intuitive as its algebra is additive rather than subtractive (like the one we have with paints). Then HSV is a middle ground to be more practical for humans, as it separates the color into its 3 most significant dimensions, that are value, hue, and saturation. It does so while being a fast linear transform, but it is not a really good mapping with regards to human perception. For example a given fixed value will appear as very different when given two different hues. Still, it's a nice middle ground that made it a good choice for painting and image manipulation software. There are other spaces that are "more" perceptual, in that changing the hue of a color should not affect how its value is perceived. This can be useful in design work as a palette could be hue-shifted and always stay legible, which was not possible in the general case with HSV or RGB. Yet, these fancy color spaces are not used a lot because in most practical applications there isn't enough justifications to use them. In particular because professionals are used to workaround the space deficiencies, so there's a cost to re-learn some of the primitives. The only really practical application I have ever seen of these perceptual models is to simulate 'color blindness', which theoretically give the possibility to design charts and maps that are more accessible to people. I believe such a validation tool should be required for public communications. The article is interesting and well written, as it gives an history of how some of these abstractions were developed, and highlight some of its shortcomings.