Vector Quantization and Signal Compression

  • Allen Gersho
  • Robert M. Gray
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 159)

Table of contents

  1. Front Matter
    Pages i-xxii
  2. Introduction

    1. Front Matter
      Pages 1-1
    2. Allen Gersho, Robert M. Gray
      Pages 1-13
  3. Basic Tools

    1. Front Matter
      Pages 15-15
    2. Allen Gersho, Robert M. Gray
      Pages 17-47
    3. Allen Gersho, Robert M. Gray
      Pages 49-81
    4. Allen Gersho, Robert M. Gray
      Pages 83-129
  4. Scalar Coding

    1. Front Matter
      Pages 131-131
    2. Allen Gersho, Robert M. Gray
      Pages 133-172
    3. Allen Gersho, Robert M. Gray
      Pages 173-202
    4. Allen Gersho, Robert M. Gray
      Pages 203-223
    5. Allen Gersho, Robert M. Gray
      Pages 225-257
    6. Allen Gersho, Robert M. Gray
      Pages 259-305
  5. Vector Coding

    1. Front Matter
      Pages 307-307
    2. Allen Gersho, Robert M. Gray
      Pages 309-343
    3. Allen Gersho, Robert M. Gray
      Pages 345-405
    4. Allen Gersho, Robert M. Gray
      Pages 407-485
    5. Allen Gersho, Robert M. Gray
      Pages 487-517
    6. Allen Gersho, Robert M. Gray
      Pages 519-553
    7. Allen Gersho, Robert M. Gray
      Pages 555-586

About this book

Introduction

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.

Keywords

Jitter Modulation Signal analog coding complexity computer data compression entropy information simulation

Authors and affiliations

  • Allen Gersho
    • 1
  • Robert M. Gray
    • 2
  1. 1.University of CaliforniaSanta BarbaraUSA
  2. 2.Stanford UniversityUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4615-3626-0
  • Copyright Information Kluwer Academic Publishers 1992
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-6612-6
  • Online ISBN 978-1-4615-3626-0
  • Series Print ISSN 0893-3405
  • About this book