Publisher's Synopsis
"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 importanttools in modern computing, and there has been tremendous progressin 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 Salomonis 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 Securityand Transformations and Projections in Computer Graphics.
