In this paper a competitive learning scheme for color image quantization is elaborated, in which the dithering process to eliminate 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. A class of quantization techniques performs clustering of the color space. Here the color data is subdivided into a set of clusters and each cluster is represented by one palette color. Other clustering algorithms have been proposed.