Efficient statistical computations for optimal color quantization

This chapter discusses efficient statistical computations for optimal color quantization. Color quantization is a must when using an inexpensive 8-bit color display to display high-quality color images. Even when 24-bit full color displays become commonplace in the future, quantization will still be important because it leads to significant image data compression, making extra frame buffer available for animation and reducing bandwidth requirements. Color quantization is a 3D clustering process. A color image in an RGB mode corresponds to a three-dimensional discrete density. In this chapter, quantization based on variance minimization is discussed. Efficient computations of color statistics are described. An optimal color quantization algorithm is presented. The algorithm was implemented on a SUN 3/80 workstation. It took only 10 s to quantize a 256 × 256 image. The impact of optimizing partitions is very positive. The new algorithm achieved, on average, one-third and one-ninth of mean-square errors for the median-cut and Wan et. al. algorithms, respectively.