A FUZZY CMAC MODEL FOR COLOR REPRODUCTION

Color reproduction is a complex nonlinear mapping problem due to gamut mismatch, resolution conversion, quantization, nonlinear color relati onship between scanner and printer. To solve such a complex problem in color reproduction, this paper proposes a fuzzy CMAC model, which ado pts a special parallel fuzzy inference-like process to realize the fun ction similar to higher-order CMAC. In this model, recursive B-spline receptive field functions are replaced by fuzzy sets with bell-shaped membership function, and the weights to evaluate output values are als o not crisp values but fuzzy sets. The learning algorithm is based on the maximum gradient method. For the situations of insufficiently or i rregularly distributed training patterns, this paper develops a sampli ng method to generate uniformly distributed training patterns. Accordi ng to experimental results, the proposed fuzzy CMAC model has shown it s effectiveness on color reproduction and general function approximati ons. Besides, it has advantages of fast learning speed, simple computa tion, and high stability on model parameters. (C) 1997 Elsevier Scienc e B.V.