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The Data Compression Book Mark Nelson



EBook NameThe Data Compression Book Mark Nelson
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Data Compression The Complete Reference 4th Edition (2007)

A wonderful treasure chest of information; spanning a wide range of data compression methods, from simple test compression methods to the use of wavelets in image compression. It is unusual for a text on compression to cover the field so completely." � ACM Computing Reviews "Salomon�s book is the most complete and up-to-date reference on the subject. The style, rigorous yet easy to read, makes this book the preferred choice � [and] the encyclopedic nature of the text makes it an obligatory acquisition by our library." � Dr Martin Cohn, Brandeis University Data compression is one of the most important tools in modern computing, and there has been tremendous progress in all areas of the field. This fourth edition of Data Compression provides an all-inclusive, thoroughly updated, and user-friendly reference for the many different types and methods of compression (especially audio compression, an area in which many new topics covered in this revised edition appear). Among the important features of the book are a detailed and helpful taxonomy, a detailed description of the most common methods, and discussions on the use and comparative benefits of different methods. The book�s logical, clear and lively presentation is organized around the main branches of data compression. Topics and features: �highly inclusive, yet well-balanced coverage for specialists and nonspecialists �thorough coverage of wavelets methods, including SPIHT, EZW, DjVu, WSQ, and JPEG 2000 �comprehensive updates on all material from previous editions And these NEW topics: �RAR, a proprietary algorithm �FLAC, a free, lossless audio compression method �WavPack, an open, multiplatform audio-compression algorithm �LZMA, a sophisticated dictionary-based compression method �Differential compression �ALS, the audio lossless coding algorithm used in MPEG-4 �H.264, an advanced video codec, part of the huge MPEG-4 project �AC-3, Dolby's third-generation audio codec �Hyperspectral compression of 3D data sets This meticulously enhanced reference is an essential resource and companion for all computer scientists; computer, electrical and signal/image processing engineers; and scientists needing a comprehensive compilation of compression methods. It requires only a minimum of mathematics and is well-suited to nonspecialists and general readers who need to know and use this valuable content. David Salomon is a professor emeritus of computer Science at California State University, Northridge. He has authored numerous articles and books, including Coding for Data and Computer Communications, Guide to Data Compression Methods, Data Privacy and Security, Computer Graphics and Geometric Modeling, Foundations of Computer Security and Transformations and Projections in Computer Graphics.

Introduction to Data Compression, Third Edition

Review
The need to efficiently store, manipulate, and transmit large masses of information is growing more rapidly than the capacity of systems to handle it. Engineers and computer scientists need a solid understanding of compression in order to work with the burgeoning variety of data types and increasingly data-intensive applications. This uniquely comprehensive book explains the fundamental theories and techniques of data compression, with the most complete coverage available of both lossy and lossless methods. Rather than simply describing current approaches, Sayood explains the theoretical underpinnings of the algorithms so that readers learn how to model structures in data and design compression packages of their own. Practitioners, researchers, and students will benefit from the balanced presentation of theoretical material and implementations.

Features:
* Covers both lossy and lossless compression techniques with applications to image, speech, text, audio, and video compression.
* Official compression standards for video, audio, text, and facsimile are discussed in order to illustrate the techniques: includes JPEG, MPEG, G.728, H.261, and Group 3 and 4 fax standards.
* Detailed examples follow each new concept or algorithm.
* Software implementations and sample data sets are available, allowing readers to work through the examples in the book and to experiment with various compression techniques on their own.
* Optional starred sections provide enhanced technical or theoretical discussions.
* Appendices on probability theory, random processes, and matrix concepts are included for reference.

Handbook of Data Compression

Data compression is one of the most important fields and tools in modern computing. From archiving data, to CD-ROMs, and from coding theory to image analysis, many facets of modern computing rely upon data compression. This book provides a comprehensive reference for the many different types and methods of compression. Included are a detailed and helpful taxonomy, analysis of most common methods, and discussions on the use and comparative benefits of methods and description of "how to" use them. Detailed descriptions and explanations of the most well-known and frequently used compression methods are covered in a self-contained fashion, with an accessible style and technical level for specialists and non-specialists.

Data Compression for Real Programmers

In life, time is money, and on the Internet, the size of data is money. Small programs and small files take less disk space and cost less to send over the Internet. Compression Algorithms for Real Programmers describes the basic algorithms and approaches for compressing information so you can create the smallest files possible. These new algorithms are making it possible for people to take impossibly large audio and video files and compress them enough that they can flow over the Internet.

Biographies in Data Compression

Biographies in Data Compression

Handbook of Data Compression, 5th Edition

This volume extends the 4th edition of "Data Compression: The Complete Reference". It features a different chapter structure, much new material, and many small improvements. The following new topics were added:

� The topic of compression benchmarks has been added to the Introduction.

� The paragraphs titled "How to Hide Data" in the Introduction show how data compression can be utilized to quickly and efficiently hide data in plain sight in our computers.

� Several paragraphs on compression curiosities have also been added to the Introduction.

� The new Section 1.1.2 shows why irreversible compression may be useful in certain situations.

� Chapters 2 through 4 discuss the all-important topic of variable-length codes. These chapters discuss basic, advanced, and robust variable-length codes. Many types of VL codes are known, they are used by many compression algorithms, have different properties, and are based on different principles. The most-important types of VL codes are prefix codes and codes that include their own length.

� Section 2.9 on phased-in codes was wrong and has been completely rewritten. An example of the start-step-stop code (2, 2,\infty) has been added to Section 3.2.

� Section 3.5 is a description of two interesting variable-length codes dubbed recursive bottom-up coding (RBUC) and binary adaptive sequential coding (BASC). These codes represent compromises between the standard binary (beta) code and the Elias gamma codes.

� Section 3.28 discusses the original method of interpolative coding whereby dynamic variable-length codes are assigned to a strictly monotonically increasing sequence of integers.

� Section 5.8 is devoted to the compression of PK (packed) fonts. These are older bitmaps fonts that were developed as part of the huge TeX project. The compression algorithm is not especially efficient, but it provides a rare example of run-length encoding (RLE) without the use of Huffman codes.

� Section 5.13 is about the Hutter prize for text compression.

� PAQ (Section 5.15) is an open-source, high-performance compression algorithm and free software that features sophisticated prediction combined with adaptive arithmetic encoding. This free algorithm is especially interesting because of the great interest it has generated and because of the many versions, subversions, and derivatives that have been spun off it.

� Section 6.3.2 discusses LZR, a variant of the basic LZ77 method, where the lengths of both the search and look-ahead buffers are unbounded.

� Section 6.4.1 is a description of LZB, an extension of LZSS. It is the result of evaluating and comparing several data structures and variable-length codes with an eye to improving the performance of LZSS.

� SLH, the topic of Section 6.4.2, is another variant of LZSS. It is a two-pass algorithm where the first pass employs a hash table to locate the best match and to count frequencies, and the second pass encodes the offsets and the raw symbols with Huffman codes prepared from the frequencies counted by the first pass.

� Most LZ algorithms were developed during the 1980s, but LZPP, the topic of Section 6.5, is an exception. LZPP is a modern, sophisticated algorithm that extends LZSS in several directions and has been inspired by research done and experience gained by many workers in the 1990s. LZPP identifies several sources of redundancy in the various quantities generated and manipulated by LZSS and exploits these sources to obtain better overall compression.

� Section 6.14.1 is devoted to LZT, an extension of UNIX compress/LZC. The major innovation of LZT is the way it handles a full dictionary.

� LZJ (Section 6.17) is an interesting LZ variant. It stores in its dictionary, which can be viewed either as a multiway tree or as a forest, every phrase found in the input. If a phrase is found n times in the input, only one copy is stored in the dictionary. Such behavior tends to fill the dictionary up very quickly, so LZJ limits the length of phrases to a preset parameter h.

� The interesting, original concept of antidictionary is the topic of Section 6.31. A dictionary-based encoder maintains a list of bits and pieces of the data and employs this list to compress the data. An antidictionary method, on the other hand, maintains a list of strings that do not appear in the data. This generates negative knowledge that allows the encoder to predict with certainty the values of many bits and thus to drop those bits from the output, thereby achieving compression.

� The important term "pixel" is discussed in Section 7.1, where the reader will discover that a pixel is not a small square, as is commonly assumed, but a mathematical point.

� Section 7.10.8 discusses the new HD photo (also known as JPEG XR) compression method for continuous-tone still images.

� ALPC (adaptive linear prediction and classification), is a lossless image compression algorithm described in Section 7.12. ALPC is based on a linear predictor whose coefficients are computed for each pixel individually in a way that can be mimiced by the decoder.

� Grayscale Two-Dimensional Lempel-Ziv Encoding (GS-2D-LZ, Section 7.18) is an innovative dictionary-based method for the lossless compression of grayscale images.

� Section 7.19 has been partially rewritten.

� Section 7.40 is devoted to spatial prediction, a combination of JPEG and fractal-based image compression.

� A short historical overview of video compression is provided in Section 9.4.

� The all-important H.264/AVC video compression standard has been extended to allow for a compressed stream that supports temporal, spatial, and quality scalable video coding, while retaining a base layer that is still backward compatible with the original H.264/AVC. This extension is the topic of Section 9.10.

� The complex and promising VC-1 video codec is the topic of the new, long Section 9.11.

� The new Section 11.6.4 treats the topic of syllable-based compression, an approach to compression where the basic data symbols are syllables, a syntactic form between characters and words.

� The commercial compression software known as stuffit has been around since 1987. The methods and algorithms it employs are proprietary, but some information exists in various patents. The new Section 11.16 is an attempt to describe what is publicly known about this software and how it works.

� There is a short appendix that presents and explains the basic concepts and terms of information theory.

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