Ebook: Vector Quantization and Signal Compression
- Tags: Electrical Engineering, Signal Image and Speech Processing
- Series: The Springer International Series in Engineering and Computer Science 159
- Year: 1992
- Publisher: Springer US
- Edition: 1
- Language: English
- pdf
Herb Caen, a popular columnist for the San Francisco Chronicle, recently quoted a Voice of America press release as saying that it was reorganizing in order to "eliminate duplication and redundancy. " This quote both states a goal of data compression and illustrates its common need: the removal of duplication (or redundancy) can provide a more efficient representation of data and the quoted phrase is itself a candidate for such surgery. Not only can the number of words in the quote be reduced without losing informa tion, but the statement would actually be enhanced by such compression since it will no longer exemplify the wrong that the policy is supposed to correct. Here compression can streamline the phrase and minimize the em barassment while improving the English style. Compression in general is intended to provide efficient representations of data while preserving the essential information contained in the data. 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 (excluding other data types such as financial data or general purpose computer data). 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.
Content:
Front Matter....Pages i-xxii
Front Matter....Pages 1-1
Introduction....Pages 1-13
Front Matter....Pages 15-15
Random Processes and Linear Systems....Pages 17-47
Sampling....Pages 49-81
Linear Prediction....Pages 83-129
Front Matter....Pages 131-131
Scalar Quantization I: Structure and Performance....Pages 133-172
Scalar Quantization II:Optimality and Design....Pages 173-202
Predictive Quantization....Pages 203-223
Bit Allocation and Transform Coding....Pages 225-257
Entropy Coding....Pages 259-305
Front Matter....Pages 307-307
Vector Quantization I:Structure and Performance....Pages 309-343
Vector Quantization II:Optimality and Design....Pages 345-405
Constrained Vector Quantization....Pages 407-485
Predictive Vector Quantization....Pages 487-517
Finite—State Vector Quantization....Pages 519-553
Tree and Trellis Encoding....Pages 555-586
Adaptive Vector Quantization....Pages 587-629
Variable Rate Vector Quantization....Pages 631-689
Back Matter....Pages 691-732
Content:
Front Matter....Pages i-xxii
Front Matter....Pages 1-1
Introduction....Pages 1-13
Front Matter....Pages 15-15
Random Processes and Linear Systems....Pages 17-47
Sampling....Pages 49-81
Linear Prediction....Pages 83-129
Front Matter....Pages 131-131
Scalar Quantization I: Structure and Performance....Pages 133-172
Scalar Quantization II:Optimality and Design....Pages 173-202
Predictive Quantization....Pages 203-223
Bit Allocation and Transform Coding....Pages 225-257
Entropy Coding....Pages 259-305
Front Matter....Pages 307-307
Vector Quantization I:Structure and Performance....Pages 309-343
Vector Quantization II:Optimality and Design....Pages 345-405
Constrained Vector Quantization....Pages 407-485
Predictive Vector Quantization....Pages 487-517
Finite—State Vector Quantization....Pages 519-553
Tree and Trellis Encoding....Pages 555-586
Adaptive Vector Quantization....Pages 587-629
Variable Rate Vector Quantization....Pages 631-689
Back Matter....Pages 691-732
....