USING VECTOR QUANTIZATION FOR IMAGE-PROCESSING

Image compression is the process of reducing the number of bits requir ed to represent an image. Vector quantization, the mapping of pixel in tensity vectors into binary vectors indexing a limited number of possi ble reproductions, is a popular image compression algorithm. Compressi on has traditionally been done with little regard for image processing operations that may precede or follow the compression step. Recent wo rk has used vector quantization both to simplify image processing task s-such as enhancement, classification, halftoning, and edge detection- and to reduce the computational complexity by performing them simultan eously with the compression. After briefly reviewing the fundamental i deas of vector quantization, we present a survey of vector quantizatio n algorithms that perform image processing.