Approximating the CIECAM97s color appearance model by means of neural networks

摘要

Since the context in which colors are seen on the monitor is very different from that in which they are seen when printed, color imaging demands a reliable color appearance model. We present a method for faithfully approximating the color appearance model CIECAM97s by means of feed-forward neural networks trained with the error back-propagation algorithm. In particular, we show that it is sufficient to train a single neural network to approximate the combination of the forward and reverse CIECAM97s models independently by the adopted whites and the type of medium (CRT and hard copy).