Evolutionary strategies for adaptive color quantization

Color quantization of still images can be easily stated as a clustering problem. Color quantization of sequences of images becomes a non-stationary clustering problem. In this paper we propose a very simple and effective evolutive strategy to perform adaptively the computation of the color representatives for each image in the sequence. Salient features of the evolutive strategy proposed here are: individuals correspond to individual cluster centres, to approach real-time response we impose one-generation adaptation for each image, only mutation operators are applied and these mutation operators are guided by the actual covariance matrices of the clusters. Experimental results on a sequence of indoor images are presented.