Determining optimum subband edges for signal compression

S. Jana, A. Makur
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Abstract

The coding gain in subband coding, a popular technique for achieving signal compression, depends on how the input signal spectrum is decomposed into subbands. The optimality of such decomposition is conventionally addressed by designing appropriate filter banks. The issue of optimal decomposition of the input spectrum is addressed by choosing the set of band that, for a given number of bands, will achieve maximum coding gain. A set of necessary conditions for such optimality is derived, and an algorithm to determine the optimal band edges is then proposed. These band edges along with ideal filters, achieve the upper bound of coding gain for a given number of bands. It is shown that with ideal filters, as well as with realizable filters for some given effective length, such a decomposition system performs better than the conventional nonuniform binary tree-structured decomposition in some cases for AR sources as well as images.
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确定信号压缩的最佳子带边缘
子带编码是实现信号压缩的一种常用技术,其编码增益取决于输入信号频谱如何被分解成子带。这种分解的最优性通常通过设计适当的滤波器组来解决。输入频谱的最优分解问题是通过选择一组频带来解决的,对于给定的频带数量,该频带将获得最大的编码增益。导出了这种最优性的一组必要条件,并提出了一种确定最优带边的算法。这些频带边缘与理想滤波器一起,实现给定频带数量的编码增益上限。结果表明,对于理想滤波器,以及给定有效长度的可实现滤波器,在某些情况下,对于AR源和图像,这种分解系统的性能优于传统的非均匀二叉树结构分解。
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