This book is devoted to the theory and practice of signal compression; i.e. data compression applied to signals such as speech, audio, images and video signals. The emphasis is on the conversion of analog waveforms into efficient digital representations and on the compression of digital information into the fewest possible bits. Both operations should yield the highest possible reconstruction fidelity subject to constraints on the bit rate and implementation complexity. The conversion of signals into such efficient digital representations has several goals: to minimize the communication capacity required for transmission of high quality signals such as speech and images or, equivalently, to obtain the best possible fidelity over an available communication channel; to minimize the storage capacity required for saving such information in fast storage media and in archival data bases or, equivalently, to obtain the best possible quality for the largest amount of information stored in a given medium; to provide the simplest possible accurate descriptions of a signal so as to minimize the subsequent complexity of signal processing algorithms such as classification, transformation and encryption. In addition to these common goals of communication, storage, and signal processing systems, efficient coding of both analog and digital information is intimately connected to a variety of other fields such as pattern recognition, image classification, speech recognition, cluster analysis regression, and decision tree design. Thus techniques from each field can often be extended to another and combined signal processing operations can take advantage of the similar algorithm structures and designs. This book has been written for use in a graduate course on quantization and signal compression and represents the most comprehensive reference available for research scientists and practitioners working in fields related to the topic.
Vector Quantization and Signal Compression
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Most Helpful Customer Reviews
5 of 5 people found the following review helpful:
5.0 out of 5 stars
The most complete book on vector quantization,
By Jean (Belgium) - See all my reviews
This review is from: Vector Quantization and Signal Compression (The Springer International Series in Engineering and Computer Science) (Hardcover)
An essential book for researchers and engineers working on vector quantization. It provides a (nearly) exhaustive description of the available VQ methods, with analyses and discussions. The book concentrates on VQ, so don't buy it if you're not interested in that only. Most math tools explained. Could be a little bit outdated on some aspects -> things are moving fast in the field.
5.0 out of 5 stars
This is a very good book for students and engineers.,
By A Customer
This review is from: Vector Quantization and Signal Compression (The Springer International Series in Engineering and Computer Science) (Hardcover)
Many useful concepts of digital compression can be found in this book. It is easy to read and understand, especially for students and engineers in EE.
3 of 5 people found the following review helpful:
3.0 out of 5 stars
Comprehensive but marred by poor printing,
By Moosh (Seattle, WA USA) - See all my reviews
This review is from: Vector Quantization and Signal Compression (The Springer International Series in Engineering and Computer Science) (Hardcover)
This book appears to be a "print on demand" style book which manifests itself, in this case, as a poor quality hardcover. Some of the text is laughably bad, the few images near the end look like they are snapshots from a black and white TV screen, but most bothersome is the "muddy" look of the text. The price seems a bit steep for such a poor quality print. That said, the actual content is very comprehensive. One of the authors (Gray) is co-creator of the now commonplace LBG (Linde Buzo Gray) VQ algorithm. Fortunately, the quality of the content shines through the terrible printing.
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Inside This Book
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Key Phrases - Statistically Improbable Phrases (SIPs):
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entropy coded, super codebook, optimal prediction error filter, regular quantizer, variable rate vector quantization, compandor model, codebook design procedure, minimum distortion encoder, ith quantizer, random processes and linear systems, encode the training sequence, recursive decoder, minimum distortion path, noiseless code, predictive vector quantizer, candidate code vectors, neighbor code vector, noiseless source code, prediction error polynomial, signal coding system, extended codebook, classifier codebook, residual codebook, overall average distortion, ordinary memoryless Key Phrases - Capitalized Phrases (CAPs): (learn more)
Gauss Markov, Input String Index, Shannon Bound, Monte Carlo, Gauss-Markov Source, Design Step, Nonlinear Interpolative, North American, Predictive Complete New!
Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
entropy coded, super codebook, optimal prediction error filter, regular quantizer, variable rate vector quantization, compandor model, codebook design procedure, minimum distortion encoder, ith quantizer, random processes and linear systems, encode the training sequence, recursive decoder, minimum distortion path, noiseless code, predictive vector quantizer, candidate code vectors, neighbor code vector, noiseless source code, prediction error polynomial, signal coding system, extended codebook, classifier codebook, residual codebook, overall average distortion, ordinary memoryless Key Phrases - Capitalized Phrases (CAPs): (learn more)
Gauss Markov, Input String Index, Shannon Bound, Monte Carlo, Gauss-Markov Source, Design Step, Nonlinear Interpolative, North American, Predictive Complete New!
Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
100
books
cite this book:
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- Multidimensional Signal, Image, and Video Processing and Coding by John W. Woods on page 70, and page 315
- Speech and Audio Coding for Wireless and Network Applications (The Springer International Series in Engineering and Computer Science) by Bishnu S. Atal in Front Matter, and page 159
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