Rate-Distortion Coding Simulation for Color Images

We propose a distortion measure for color images, based on a mathematical model of color vision, and supported by subjective image quality evaluations. The visual model is configured after a simplified schematic of the retina's physiology and it transforms the red, green and blue image components into a representation that is consistent with major psychophysical phenomena. The distortion criterion proposed consists of measuring the mean square error in the above representation space. Consistency of the measure with human quality judgment is supported by a subjective ranking experiment, using images distorted in various ways by addition of noise. An optimal coder (in the rate distortion sense) is also simulated, which minimizes the distortion measured as proposed. The resulting image provides a quality standard at the rate distortion bound, against which actual coders can be compared. Finally it is observed that from a statistical point of view, the model's output is a near ideal color image representation for efficient coding.