A JOINTLY OPTIMIZED SUBBAND CODER

The mainstream approach to subband coding has been to partition the in put signal into subband signals and to code those signals separately w ith optimal or near-optimal quantizers and entropy coders. A more effe ctive approach, however, is one where subband coders are optimized joi ntly so that the average distortion introduced by the subband quantize rs is minimized subject to a constraint on the output rate of the subb and encoder. In this paper, a subband coder with jointly optimized mul tistage residual quantizers and entropy coders is introduced and appli ed to image coding. The high performance of the coder is attributed to its ability to exploit statistical dependencies within and across the subbands. The efficiency of the multistage residual quantization stru cture and the effectiveness of the statistical modeling algorithm resu lt in an attractive balance among reproduction quality, rate, and comp lexity.