DCT-Based Codebook Design for Vector Quantization of Images

A new codebook design algorithm based on a two-dimensional discrete cosine transform (2-D DCT) is presented for vector quantization (VQ) of images. The significant features of training images are extracted by using the 2-D DCT. A codebook is generated by partitioning the training set into a binary tree, Each training vector at a nonterminal node of the binary tree is directed to one of the two descendants by comparing a single feature associated with that node to a threshold. Compared with the pairwise nearest neighbor (PNN) algorithm, the new algorithm results in a considerable reduction in computation time and shows better picture quality.