Yes exactly. I'm intentionally using "color" as a perceptual thing, not as a physical thing. If we are talking about a color model, then it needs to model perception. As such, RGB, as a predictor of perception, can often fail because it doesn't account for much more than what hits the retina, not what happens after. For one, it lacks spatial context - placing the same RGB value with a different surround will feel different, like in the example above. But if you had a real color (as-in, perceptual) picker in Photoshop, you would get a different value.It's excellent at compressing the visible part of the EM spectrum, however. This is what I meant by stimuli encoding.
dahart|3 months ago
I find it confusing to claim that cone response isn’t color yet, that’s going to get you in trouble in serious color discussions. Maybe better to just be careful and qualify that you’re talking about perception than say something that is highly contestable?
The claim that a color model must model perception is also inaccurate. Whether to incorporate human perception is a choice that is a goal in some models. Having perceptual goals is absolutely not a requirement to designing a practical color model, that depends entirely on the design goals. It’s perfectly valid to have physical color models with no perceptual elements.
subb|3 months ago
And so when I say "color" I only mean it to be the construction that we make out of the physical thing.
We project back these construction outside of us (e.g. the apple is red), but we must no fool ourselves that the projection is the thing, especially when we try to be more precise about what is happening.
This is why I'm saying a 3D model of color (brain thing) is very far from modelling color (brain thing) at all. But! It's not purely physical either, otherwise it would just be a spectral band or something. So this is pseudo-perceptual. It's the physical stuff, tailored for the very first bits of anatomy that we have to read this physical stuff. It's stimuli encoding.
If you build a color model, it's therefore always perceptual, and needs to be evaluated against what you are trying to model - perception. You create a model to predict things. RGB and all the other models based on three values in a vaccum will always fail at predicting color (brain!) when the stimuli's surround is more complex.