约束小波包的树状结构视频编码算法

H. Khalil, A. Jacquin, C. Podilchuk
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引用次数: 11

摘要

传统的小波包优化技术忽略了压缩方案中有损部分的结构信息。然而,这些信息可以帮助指导优化过程,从而产生高效的WP结构。我们提出了一种具有约束率失真优化的小波包算法,使其适用于后续的树结构编码,如分层树中的集合划分(SPMT)算法。(八度频带)小波变换适用于简单而连贯的树形空间关系,然后可用于定义零树。然而,输入图像具有不同的频率分布,而像WP这样的自适应变换必然会在逐幅图像的基础上更有效。使用小波变换算法,小波变换域中的系数可以重新排列以产生类似(或模拟)正常小波变换结构的东西。执行这个阶段通常是为了简化编码阶段。然而,无约束优化可能导致变换后的图像具有复杂或不连贯的树状空间关系。这项工作的目的是表明嵌入式编码器的效率,如SPMT和夏皮罗的零树在很大程度上依赖于具有相干空间树关系的WP结构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Constrained wavelet packets for tree-structured video coding algorithms
Traditional wavelet packet (WP) optimization techniques neglect information about the structure of the lossy part of the compression scheme. Such information, however, can help guide the optimization procedure so as to result in efficient WP structures. We propose a wavelet packet algorithm with a constrained rate-distortion optimization which makes it suited to subsequent tree-structured coding such as with the set partitioning in hierarchical trees (SPMT) algorithm. The (octave-band) wavelet transform lends itself to simple and coherent tree-shaped spatial relations which can then be used to define zero-trees. Yet, input images have different frequency distributions and an adaptive transform such as WP is bound to be more efficient on an image-by-image basis. With WP algorithms, the coefficients in the WP domain can be rearranged to produce what resembles (or simulates) the normal wavelet transform structure. This stage is usually performed to simplify the coding stage. However, an unconstrained optimization can result in a transformed image with complicated or incoherent tree-shaped spatial relations. This work aims to show that the efficiency of embedded coders such as SPMT and Shapiro's Zerotrees strongly depends on WP structures with coherent spatial tree relationships.
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