yan@xxxxxxxxxxxxxxxxx wrote:
When you write "by hand" you mean, that I need to write another tool by myself. Of course, it's kind of an aswer :-) But this is rather hard thing. And, on the other hand, I think that only slighter code changes are needed.
There are several paths available to you. You could code it in C using (Argyll) icclib. You could probably do it even easier using lcms, and lcms may have scripting interfaces available if you want to use something other than C (ie. lcms-python, tcllcms etc.).
Coolproof in matrix+gamma mode reads ".ti3" values and try to 1. Guess gamma values;
No, it doesn't do any guessing. If fits a response curve to the device behaviour exemplified by the .ti3 data points.
The only key I need is "not to guess gamma upon ti3 values, and assume gamma is [some value]". The linearity of camera sensor is quite a good assumption. By analizing this or that real data you get "gamma 2.18" or "gamma 2.21", and this number would be not exactly 2.2 only beacause of camera noise.
This is what I mean by colprof not being the ideal tool. It fits the profile to the data as given, using a least squares type fit criteria. One workaround would be to process your data values to be linear light and then use the -am option to fit the matrix only. You would then have to patch the profile and change the gamma value in the R,G & B curve tags to be the gamma you know it to be. Graeme Gill.