Last year at HVEI, I presented a computational model of lightness perception inspired by data from primate neurophysiology. That model first encodes local spatially-directed local contrast in the image, then integrates the resulting local contrast signals across space to compute lightness (Rudd, J Percept Imaging, 2020; HVEI Proceedings, 2021). Here I computer simulate the lightness model and generalize it to model color perception by including in the model local color contrast detectors that have properties similar to those of cortical “double-opponent” (DO) neurons. DO neurons make local spatial comparisons between the activities of L vs M and S vs (L + M) cones and half-wave rectify these local color contrast comparisons to produce psychophysical channels that encode, roughly, amounts of ‘red,’ ‘green’, ‘blue’, and ‘yellow.”