Set Partition Coding: Part II of Set Partition Coding and Image Wavelet Coding Systems

W. Pearlman, A. Said
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引用次数: 19

Abstract

This monograph describes current-day wavelet transform image coding systems. As in the first part, steps of the algorithms are explained thoroughly and set apart. An image coding system consists of several stages: transformation, quantization, set partition or adaptive entropy coding or both, decoding including rate control, inverse transformation, de-quantization, and optional processing (see Figure 1.6). Wavelet transform systems can provide many desirable properties besides high efficiency, such as scalability in quality, scalability in resolution, and region-of-interest access to the coded bitstream. These properties are built into the JPEG2000 standard, so its coding will be fully described. Since JPEG2000 codes subblocks of subbands, other methods, such as SBHP (Subband Block Hierarchical Partitioning) [3] and EZBC (Embedded Zero Block Coder) [8], that code subbands or its subblocks independently are also described. The emphasis in this part is the use of the basic algorithms presented in the previous part in ways that achieve these desirable bitstream properties. In this vein, we describe a modification of the tree-based coding in SPIHT (Set Partitioning In Hierarchical Trees) [15], whose output bitstream can be decoded partially corresponding to a designated region of interest and is simultaneously quality and resolution scalable. This monograph is extracted and adapted from the forthcoming textbook entitled Digital Signal Compression: Principles and Practice by William A. Pearlman and Amir Said, Cambridge University Press, 2009.
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集分割编码:集分割编码与图像小波编码系统的第二部分
这本专著描述了当前的小波变换图像编码系统。与第一部分一样,算法的步骤进行了彻底的解释并进行了区分。图像编码系统包括变换、量化、集合分割或自适应熵编码或两者同时进行的几个阶段,解码包括速率控制、逆变换、去量化和可选处理(见图1.6)。小波变换系统除了效率高外,还能提供许多理想的特性,如质量的可扩展性、分辨率的可扩展性和对编码比特流的兴趣区域访问。这些属性内置于JPEG2000标准中,因此将对其编码进行完整描述。由于JPEG2000对子带的子块进行编码,因此还描述了对子带或其子块进行独立编码的其他方法,如shbhp (Subband Block Hierarchical Partitioning)[3]和EZBC (Embedded Zero Block Coder)[8]。本部分的重点是使用前一部分中介绍的基本算法来实现这些理想的比特流属性。在这方面,我们描述了SPIHT (Set Partitioning In Hierarchical Trees)[15]中基于树的编码的一种修改,其输出比特流可以部分对应于指定的感兴趣区域进行解码,同时具有质量和分辨率可扩展性。本专著摘自即将出版的教科书《数字信号压缩:原理与实践》,作者是William A. Pearlman和Amir Said,剑桥大学出版社,2009年。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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