CONDITIONAL ENTROPY-CONSTRAINED RESIDUAL VQ WITH APPLICATION TO IMAGE-CODING

This paper introduces an extension of entropy-constrained residual vec tor quantization (VQ) where intervector dependencies are exploited, Th e method, which we call conditional entropy-constrained residual VQ, e mploys a high-order entropy conditioning strategy that captures local information in the neighboring vectors, When applied to coding images, the proposed method is shown to achieve better rate-distortion perfor mance than that of entropy-constrained residual vector quantization wi th less computational complexity and lower memory requirements. Moreov er, it can be designed to support progressive transmission in a natura l way, It is also shown to outperform some of the best predictive and finite-state VQ techniques reported in the literature, This is due par tly to the joint optimization between the residual vector quantizer an d a high-order conditional entropy coder as well as the efficiency of the multistage residual VQ structure and the dynamic nature of the pre diction.