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A Concise Introduction to Data Compression (Undergraduate Topics in Computer Science) [Paperback]

David Salomon
3.0 out of 5 stars  See all reviews (2 customer reviews)

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Book Description

March 10, 2008 1848000715 978-1848000711 2008

This clearly written book offers readers a succinct foundation to the most important topics in the field of data compression. Part I presents the basic approaches to data compression and describes a few popular techniques and methods that are commonly used to compress data. The reader will discover essential concepts. Part II concentrates on advanced techniques, such as arithmetic coding, orthogonal transforms, subband transforms and Burrows-Wheeler transform. This book is the perfect reference for advanced undergraduates in computer science and requires a minimum of mathematics. An author-maintained website provides errata and auxiliary material.


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Editorial Reviews

Review

From the reviews:

"This book on data compression … can be considered an introductory one into a part of coding theory. … can be used by students who want to understand a general description of data compression and some of the important themes in this domain. … In each part exercises are provided, and solutions for them can be found at the end of the book. … Overall, the book … is particularly suitable for undergraduate students to be used for laboratory purposes." (Nicolae Constantinescu, Zentralblatt MATH, Vol. 1147, 2008)

"This book provides an overview of compression methods in general, and goes into a fair amount of detail for some specific algorithms in use. … On the whole, this could be a useful book for a short course on compression at the undergraduate level, and would provide students with a taste for the material." (Jeffrey Putnam, ACM Computing Reviews, December, 2008)

“In the present book, multiple explanations and examples are used to clarify and expose different and important concepts, such as entropy and variable length coding. The book also includes a numerous program code snippets. These programs are clearly written and so should be easily understood by students. The book is excellent and fills the stated goal. When I am going to teach data compression again, I will most definitely use A Concise Introduction to Data Compression as a textbook for the class.” (Ville Hautamäki, SIGACT News, April, 2012)

From the Back Cover

Compressing data is an option naturally selected when faced with problems of high costs or restricted space. Written by a renowned expert in the field, this book offers readers a succinct, reader-friendly foundation to the chief approaches, methods and techniques currently employed in the field of data compression.

Part I presents the basic approaches to data compression and describes a few popular techniques and methods commonly used to compress data. The reader discovers essential concepts, such as variable-length and prefix codes, statistical distributions and run-length encoding. Part II then concentrates on advanced techniques, such as arithmetic coding, orthogonal transforms, subband transforms and the Burrows-Wheeler transform.

Features:

• Clear overview of the principles underlying this field

• Outlines the essentials of the various approaches to compressing data

• Contains many learning aids such as: chapter introductions and summaries, chapter-end exercises, comprehensive glossary, etc.

• Provides several examples of important compression algorithms

• Offers a supplementary author-maintained website, with errata and auxiliary material – www.davidsalomon.name/DCugAdvertis/DCug.html

• An ideal introductory volume to David Salomon’s fourth edition of Data Compression: The Complete Reference

Complete and clear, this book is the perfect resource for undergraduates in computer science and requires a minimum of mathematics. It is also ideal for readers with a basic knowledge of computer science wanting to learn about data compression.

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, Transformations and Projections in Computer Graphics, and Variable-length Codes for Data Compression.


Product Details

  • Series: Undergraduate Topics in Computer Science
  • Paperback: 314 pages
  • Publisher: Springer; 2008 edition (March 10, 2008)
  • Language: English
  • ISBN-10: 1848000715
  • ISBN-13: 978-1848000711
  • Product Dimensions: 0.6 x 6.9 x 9.1 inches
  • Shipping Weight: 1.1 pounds (View shipping rates and policies)
  • Average Customer Review: 3.0 out of 5 stars  See all reviews (2 customer reviews)
  • Amazon Best Sellers Rank: #2,469,254 in Books (See Top 100 in Books)

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Most Helpful Customer Reviews
2 of 3 people found the following review helpful
5.0 out of 5 stars concise, precise and easy. What's not to like? October 7, 2010
Format:Paperback
I really really loved this book.

I'm a self-taught programmer, and this book is one of the easiest introductions to the subject. The language is simple, the examples are clear and unhurried, and the important topics are covered. In fact, I understood basic concepts of information theory here for the first time. For example, while everybody else says "the information content of a random variable is \sigma(P_i log(P_i))", this books takes a couple of pages to explain the intuition behind this formula.

For the fact that this is a concise guide, it packs quite a bit of information, from LZW, Huffman, zip, arithmetic coding, wavelets, jpeg and audio compression (just to pick a few). The best way to read this book is to have a calculator handy, and to hand-do the examples from the description of the algorithm _before_ you read the solution.

This is a keeper.
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4 of 9 people found the following review helpful
1.0 out of 5 stars Very hard to follow text book April 18, 2009
Format:Paperback|Verified Purchase
The author doesn't see fit to show the inputs and the outputs of each of the processes.

A terrible example is LZW. We know there is a processed buffer and a look-ahead buffer. We don't know the step-by-step process.
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