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.