Digital Signal Process. Lab., Georgia Inst. of Technol., Atlanta, GA.
IEEE Trans Image Process. 1996;5(9):1311-23. doi: 10.1109/83.535843.
The mainstream approach to subband coding has been to partition the input signal into subband signals and to code those signals separately with optimal or near-optimal quantizers and entropy coders. A more effective approach, however, is one where the subband coders are optimized jointly so that the average distortion introduced by the subband quantizers is minimized subject to a constraint on the output rate of the subband encoder. A subband coder with jointly optimized multistage residual quantizers and entropy coders is introduced and applied 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 structure and the effectiveness of the statistical modeling algorithm result in an attractive balance among the reproduction quality, rate, and complexity.
子带编码的主流方法一直是将输入信号分割成子带信号，并使用最优或近最优的量化器和熵编码器对子带信号进行单独编码。然而，一种更有效的方法是对子带编码器进行联合优化，以便在子带编码器输出率的约束下最小化子带量化器引入的平均失真。本文介绍了一种联合优化的多级剩余量化器和熵编码器的子带编码器，并将其应用于图像编码。该编码器的高性能归因于其利用子带内和子带间统计相关性的能力。多级剩余量化结构的效率和统计建模算法的有效性在再现质量、速率和复杂度之间实现了吸引人的平衡。
