图像子带编码的有损Lempel-Ziv算法

W. Finamore, M.B. de Carvalho
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引用次数: 8

摘要

讨论了有损Lempel-Ziv (LLZ)算法在图像子带编码器(SBC)上的数据压缩策略。提出了LLZ/s和LLZ/d两种LLZ方案。这个想法是在通常的SBC中替换量化器,随后是霍夫曼编码器,用于压缩几个正交镜像滤波器(QMF)输出处的图像组件,或者,通过LLZ替换矢量量化器。SBC/QH固有的设计复杂性,如滤波器输出和位分配的统计建模或矢量量化器设计,可以由SBC/LLZ方案取代,该方案省去了被压缩子带的统计知识。对这些初步方案的仿真分析表明,与其他方案相比,SBC/LLZ方案可以获得足够的性能。描述了提出的两个LLZ版本,并测试了一些图像压缩性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lossy Lempel-Ziv on subband coding of images
The use of a lossy Lempel-Ziv (LLZ) algorithm as the data compression stratagem on image subband coders (SBC) is discussed. Two LLZ schemes, namely LLZ/s and LLZ/d are proposed. The idea is to replace in the usual SBC, the bank of quantizers followed by Huffman encoder which are used to compress the image components at the output of the several quadrature mirror filters (QMF) or, alternatively, to replace the vector quantizer, by an LLZ. Design complexities inherent to the SBC/QH such as statistical modeling of the filters outputs and bit allocations or the vector quantizer design can be superseded by the SBC/LLZ scheme which dispenses with the knowledge of statistics of the subband being compressed. Simulation analysis of these preliminaries SBC/LLZ schemes have shown that an adequate performance, as compared to other schemes, can be obtained. The two LLZ versions proposed are described and some image compression performance rates are examined.<>
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