Markov system for image vector quantization coding

Vector quantization (VQ) has been accepted as one of the most effective ima ge compression methods with provable rate-distortion optimality. The output s of VQ are a collection of indices, which correspond to the addresses of t he codevectors in the codebook. The indices are, however, not mutually inde pendent. They are in fact very highly correlated and are thus appropriately described by a Markov system. In this paper, a Markov system for VQ indice s is introduced. Statistics are gathered for various scans, such as the zig -zag, Peano, row-major and column-major scans. The proposed method, like ad dress VQ, achieves the same image quality as conventional VQ. Simulation re sults show that the proposed method achieves a better bit-rate reduction th an Address-VQ. Besides. both the computational complexity and memory needed for the proposed method are lower. Nevertheless, the only extra operation needed by the proposed method is a simple table retrieval operation on both the encoder side and the decoder side. We believe that it is a method wort h further exploration. (C) 2000 Society of Photo-Optical Instrumentation En gineers.