商品の説明

The second edition of Introduction to Data Compression builds on the features that made the first the logical choice-for practitioners who need a comprehensive guide to compression for all types of multimedia and instructors who want to equip their students with solid foundations in these increasingly important and diverse techniques. This book provides an extensive introduction to the theory underlying today's compression techniques, with detailed, instruction for their application. All of the coverage has been updated to reflect the state of the art in data compression, including both new algorithms and older methods for which new uses are being found. And the downloadable software gives you the opportunity to see firsthand how various algorithms work, to choose and implement appropriate techniques in your own applications, and to build your own algorithms.

Features

• Fully updated to cover the most recent lossy and lossless compression techniques, including wavelets, subband coding, predictive lossless techniques, and Huffman coding variants.
• Explains established and emerging standards in depth: JPEG 2000, JPEG-LS, MPEG 2, Group 3 and 4 Faxes, JBIG 2, ADPCM, LPC, CELP, and MELP.
• Includes an new chapter providing the mathematical background required for understanding wavelets and subband coding.
• Via the companion Web site, provides source code that enables you to experiment with a wide range of compression techniques, along with sample data and updates on the latest developments in the compression field.

商品の詳細

• Amazon.co.jp ランキング: #161338 / 本
• 発売日: 2005-12-15
• オリジナル言語: 英語
• 版型: ハードカバー
• 704 ページ

内容説明
Each edition of Introduction to Data Compression has widely been considered the best introduction and reference text on the art and science of data compression, and the third edition continues in this tradition. Data compression techniques and technology are ever-evolving with new applications in image, speech, text, audio, and video. The third edition includes all the cutting edge updates the reader will need during the work day and in class.

Khalid Sayood provides an extensive introduction to the theory underlying today's compression techniques with detailed instruction for their applications using several examples to explain the concepts. Encompassing the entire field of data compression Introduction to Data Compression, includes lossless and lossy compression, Huffman coding, arithmetic coding, dictionary techniques, context based compression, scalar and vector quantization. Khalid Sayood provides a working knowledge of data compression, giving the reader the tools to develop a complete and concise compression package upon completion of his book.

* New content added on the topic of audio compression including a description of the mp3 algorithm
* New video coding standard and new facsimile standard explained
* Completely explains established and emerging standards in depth including JPEG 2000, JPEG-LS, MPEG-2, Group 3 and 4 faxes, JBIG 2, ADPCM, LPC, CELP, and MELP
* Source code provided via companion web site that gives readers the opportunity to build their own algorithms, choose and implement techniques in their own applications

Amazon.com
Khalid Sayood's textbook-style Introduction to Data Compression is the definitive guide to all kinds of compression schemes. Early chapters establish the mathematics involved in basic compression techniques, including lossless and lossy compression as well as the fundamentals of information theory that lay the groundwork for common forms of compression. (The book contains all the relevant formulas, although those who don't need such mathematical detail will still be able to understand the book.)

A good portion of the book examines various compression schemes, their strengths and weaknesses, and what content they work best for. Introduction to Data Compression begins with lossless compression schemes, which lose no information during the compression/decompression process. Huffman Coding, a well-established compression scheme, and arithmetic and dictionary coding also receive excellent treatment. In addition, the author takes on lossless compression for images.

For lossy compression, Sayood discusses schemes that use quantization, where a range of values is compressed in some way. He also describes scalar, vector, and differential encoding and fractal compression. A final chapter looks at video encryption (which often combines techniques from earlier chapters). Many of the compression schemes include examples from image and sound files, but the book considers a wide variety of video schemes too. This rich and confidently written text collates a lot of research and can serve as both textbook and source for designers who need a readable and mathematically solid introduction to data compression.

About the Author
Khalid Sayood received his BS and MS in Electrical Engineering from the University of Rochester in 1977 and 1979, respectively, and his Ph.D. in Electrical Engineering from Texas A&M University in 1982. In 1982, he joined the University of Nebraska, where he is the Henson Professor of Engineering. His research interests include data compression, joint source channel coding, and bioinformatics.

カスタマーレビュー

データ圧縮の入門書として最適
名前のとおりのデータ圧縮についての入門書で、データ圧縮の要素技術を詳細に解説している。この手の網羅的な解説書では、各技術の紹介に終始した結果、肝心の「その技術がなぜ圧縮に有効なのか？」という点が置き去りにされることがある。しかし本書ではこの点を安易に数式に頼らずに実例を挙げて説明しており、理解の助けとなる。（その分、分厚くて高いが）

音声符号化、静止画符号化、動画像符号化、ユニバーサル符号化の全てが取り扱われているが、中では動画像符号化の扱いが若干小さい。逆に静止画符号化がターゲットであれば、本書1冊で主要な要素技術をカバーできる。

データ圧縮の網羅的な入門書として最適

名前のとおりのデータ圧縮についての入門書で、この世界で頻繁に使用される要素技術の大部分が丁寧に解説されている。この手の網羅的な解説書では、各技術の説明に終始した結果「その技術がなぜ圧縮に有効なのか？」といった部分が置き去りにされることがある。しかし本書ではこの点を安易に数式に頼らずに実例を挙げて説明しており、理解を助ける上で非常によかった。

主としてlosslessの各方式（エントロピー符号化、辞書ベース符号化等）、静止画の圧縮方式について詳しく、JBIG2、JPEG2000等についても触れているため、これらの分野を学びたいなら値段の価値があると思う。ただし、各方式の詳細は述べられていないので、これを読んでインプリしようという方には向かない。また、動画は静止画に比してさらっと流されているため、動画圧縮について学ぶなら別の専門書を併用したほうがよいかもしれない。

explains the concepts with concrete examples.
This is one of the best book on data compression. The thing I like about this book is that it explains the concepts with concrete examples.