A near real-time Evolution-based Adaptation Strategy for dynamic Color Quantization of image sequences
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 Evolution-based Adaptive Strategy to perform the adaptive computation of the color representatives for each image in the sequence. Salient features of the algorithm proposed here are: individuals correspond to individual cluster centers, to approach real-time response we impose one-generation adaptation for each image, mutation operators are guided by the actual covariance matrices of the clusters. Experimental results on a sequence of indoor images are presented.
color quantization non-stationary clustering evolution strategy adaptive vector quantization