Codebook design algorithm for classified vector quantization based on fuzzy clustering

Classified Vector Quantization (CVQ) is used for coding images that achieves good perceptual results while reducing the computational load of the process. In this paper, image is sub-divided into 4×4 pixel blocks (vectors). Each vector is classified into an edge vector and a shade vector. Both edge vectors and shade vectors are used to design the codebooks of CVQ by Fuzzy C-Means (FCM) method. By doing so, the CVQ-FCM method can preserve the edge of image, make good image quality, and reduce the processing time while constructing the codebooks.