Abstract
A 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 algorithm results in a considerable reduction in computation time and shows better picture quality. >
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