This is not a gimp question, but perhaps there is someone here who can shed light on this issue,

How (or can you) combine errors/noise in HSV into one error/noise figure which reflects the total "human visual" error perception.

I am sure this is not a good formulation of the question. Here is another way to put it,
Take a picture I. Decompose to HSV. Now add noise Nh to H and recompose to get image I(h). Do the same for Ns to S and Nv to V.
Now, what should the relation be between Nh,Ns,Nv so that a human would say "All three images I(h). I(s) and I(v) look like they had the same amount of corruption relative to the original I.

Now I am not necessarily asking for a rigorous answer. Any reasonable heuristic would do.


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