Image and Text Compression

  • James A. Storer

Part of the The Kluwer International Series in Engineering and Computer Science book series (SECS, volume 176)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Image Compression

    1. Front Matter
      Pages 1-1
    2. Robert M. Gray, Pamela C. Cosman, Eve A. Riskin
      Pages 3-34
    3. Y. Fisher, E. W. Jacobs, R. D. Boss
      Pages 35-61
    4. John H. Reif, Akitoshi Yoshida
      Pages 63-82
  3. Text Compression

    1. Front Matter
      Pages 83-83
    2. Paul G. Howard, Jeffrey Scott Vitter
      Pages 85-112
    3. Daniel S. Hirschberg†, Debra A. Lelewer‡
      Pages 113-144
  4. Coding Theory

    1. Front Matter
      Pages 179-179
    2. Renato M. Capocelli, Alfredo De Santis
      Pages 181-213
    3. Marcelo J. Weinberger, Abraham Lempel, Jacob Ziv
      Pages 215-252
    4. Dafna Sheinwald
      Pages 253-275
  5. Back Matter
    Pages 277-354

About this book


James A. Storer Computer Science Dept. Brandeis University Waltham, MA 02254 Data compression is the process of encoding a body of data to reduce stor­ age requirements. With Lossless compression, data can be decompressed to be identical to the original, whereas with lossy compression, decompressed data may be an acceptable approximation (according to some fidelity criterion) to the original. For example, with digitized video, it may only be necessary that the decompressed video look as good as the original to the human eye. The two primary functions of data compression are: Storage: The capacity of a storage device can be effectively increased with data compression software or hardware that compresses a body of data on its way to the storage device and decompress it when it is retrieved. Communications: The bandwidth of a digital communication link can be effectively increased by compressing data at the sending end and decom­ pressing data at the receiving end. Here it can be crucial that compression and decompression can be performed in real time.


Hardware algorithms coding coding theory communication data compression modeling

Editors and affiliations

  • James A. Storer
    • 1
  1. 1.Brandeis UniversityUSA

Bibliographic information

  • DOI
  • Copyright Information Kluwer Academic Publishers 1992
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-6598-3
  • Online ISBN 978-1-4615-3596-6
  • Series Print ISSN 0893-3405
  • Buy this book on publisher's site