数据压缩导论萨尤得作者简介、书籍目录、内容摘要、编辑推荐
本书是数据压缩方面的经典著作，介绍了各种类型的压缩模式。书中首先介绍了基本压缩方法(包括无损压缩和有损压缩)中涉及的数学知识，为常见的压缩形式打牢了信息论基础，然后从无损压缩体制开始，依次讲述了霍夫曼编码、算术编码以及字典编码技术等，对于有损压缩，还讨论了使用量化的模式，描述了标量、矢量以及微分编码和分形压缩技术，最后重点介绍了视频加密。本书不但分析了各种压缩模式及其优缺点，而且还说明了它们最适合处理哪种内容。
本书非常适合从事数据压缩相关工作的专业技术人员、软硬件工程师、学生等阅读，数字图书馆、多媒体等领域的技术人员也可参考。
作者简介
作者：(美国)萨尤得 (Khalid Sayood)Khalid Sayood，著名数据压缩技术专家，内布拉斯加大学教授得克萨斯A&M大学电气工程专业博士。他的研究方向包括数据压缩、信源信道联合编码和生物信息学。
书籍目录
1 Introduction 1.1 Compression Techniques 1.1.1 Lossless Compression
1.1.2 Lossy Compression
1.1.3 Measures of Performance
1.2 Modeling and Coding
1.3 Summary
1.4 Projects and Problems 2 Mathematical Preliminaries for Lossless Compression
2.1 Overview
2.2 A Brief Introduction to Information Theory
2.2.1 Derivation of Average Information
2.3 Models
2.3.1 Physical Models
2.3.2 Probability Models
2.3.3 Markov Models
2.3.4 Composite Source Model
2.4 Coding
2.4.1 Uniquely Decodable Codes
2.4.2 Prefix Codes
2.4.3 The Kraft-McMillan Inequality
2.5 Algorithmic Information Theory
2.6 Minimum Description Length Principle
2.7 Summary
2.8 Projects and Problems 3 Huffman Coding
3.1 Overview
3.2 The Huffman Coding Algorithm
3.2.1 Minimum Variance Huffman Codes
3.2.2 Optimality of Huffman Codes
3.2.3 Length of Huffman Codes
3.2.4 Extended Huffman Codes
3.3 Nonbinary Huffman Codes
3.4 Adaptive Huffman Coding
3.4.1 Update Procedure
3.4.2 Encoding Procedure
3.4.3 Decoding Procedure
3.5 Golomb Codes
3.6 Rice Codes
3.6.1 CCSDS Recommendation for Lossless Compression
3.7 Tunstall Codes
3.8 Applications of Huffman Coding
3.8.1 Lossless Image Compression
3.8.2 Text Compression
3.8.3 Audio Compression
3.9 Summary
3.10 Projects and Problems 4 Arithmetic Coding
4.1 Overview
4.2 Introduction
4.3 Coding a Sequence
4.3.1 Generating a Tag
4.3.2 Deciphering the Tag
4.4 Generating a Binary Code
4.4.1 Uniqueness and Efficiency of the Arithmetic Code
4.4.2 Algorithm Implementation
4.4.3 Integer Implementation
4.5 Comparison of Huffman and Arithmetic Coding
4.6 Adaptive Arithmetic Coding
4.7 Applications
4.8 Summary
4.9 Projects and Problems 5 Dictionary Techniques 6 Context-Based Compression 7 Lossless Image Compression 8 Mathematical Preliminaries for Lossy Coding 9 Scalar Quantization 10 Vector Quantization 11 Differential Encoding 12 Mathematical Preliminaries for Transforms, Subbands, and Wavelets 13 Transform Coding 14 Subband Coding 15 Wavelet-Based Compression 16 Audio Coding 17 Analysis/Synthesis and Analysis by Synthesis Schemes 18 Video Compression A Probability and Random Processes B A Brief Review of Matrix Concepts C The Root Lattices Bibliography Index
章节摘录
插图：Example 9.6.1:Suppose we have a source that can be modeled as a random variable taking values in the interval [-4，4] with more probability mass near the origin than away from it. We want to quantize this using the quantizer of Figure 9.3. Let us try to flatten out this distribution using the following compander, and then compare the companded quantization with straightforward uniform quantization. The compressor characteristic we will use is given by the following equation：
媒体关注与评论
“从各方面来看，本书都无愧于数据压缩圣经的称号。新版本内容及时、精益求精。”
——Amazon读者评论
编辑推荐
数据压缩技术在网络、通信、图像处理、多媒体、数据库等诸多领域应用广泛，在现实需求推动下，近年来发展尤为迅速。《数据压缩导论(英文版·第3版)》是数据压缩领域毋庸置疑的权威指南，以内容全面、新颖而著称。书中不仅深入地阐述了各种压缩技术背后的理论、优缺点和适用范围，更通过丰富实例，详细讨论了各自的应用。书中提供了许多工具，读者足以由此自己开发出完整的压缩方案。《数据压缩导论(英文版·第3版)》特色涵盖各种常用和重要的视频、音频、文本以及传真的压缩标准。包括有损压缩和无损压缩技术在图像、语音、文本、音频以及视频压缩中的应用。增加了新的一章，讨论音频压缩，包括MP3算法。讨论了视频编码新标准，包括H.264、MPEG-4等。每个新概念或算法都辅有详细的例子。配套网站http：／／www.elsevierdirect.com／companion.jsp？ISBN=9780126208627提供软件实现源代码和实验数据。