Joint quantization and error diffusion of color images using competitive learning

Abstract

A competitive learning scheme for color image quantization is elaborated, in which the dithering process for eliminating contouring effects, instead of performed a posteriori, is imbedded in the quantization process. Quantization is performed by clustering in color space. The dithering process is a simple error diffusion which diffuses the quantization error made by one pixel to its local neighborhood. For small color palettes, this is demonstrated to improve the visual quality of quantized images.