Hi scikit-imageers, I don't have time to prepare a PR, but just as a heads-up in case anyone else wants to do so -- I wrote a complete, tested implementation of the CIECAM02 forward and inverse transforms in Python (BSD-2), which might be a nice extension to skimage.color: https://github.com/njsmith/pycam02ucs/blob/master/pycam02ucs/ciecam02.py I'm pretty confident in its correctness; the only place where it disagrees with Mark Fairchild's spreadsheet implementation, it turns out the spreadsheet is (was) wrong :-). It could probably be optimized further -- it is vectorized, but I didn't go to any great efforts to extract redundant temporaries or perform operations in-place. It's a pretty direct implementation of the equations. The API may not be exactly the scikit-image's taste ATM either -- I forget whether you prefer to use the 0-1 or 0-100 scale for XYZ (this code uses 0-100 b/c that's what the spec uses). And CIECAM02 is a weird space -- the forward transform spits out 7 named dimensions, and the inverse transform needs 3 of these, but is quite flexible about which 3, so I treat each dimension as a separate array instead of stacking them into one. That tree also has an implementation of forward and inverse transforms to the CAM02-UCS perceptually uniform space (Luo et al, 2006): https://github.com/njsmith/pycam02ucs/blob/master/pycam02ucs/cam02ucs.py -n