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Analysis of variance in statistical image processing / Ludwik Kurz and M. Hafed Benteftifa.

By: Contributor(s): Material type: TextTextPublication details: Cambridge ; New York : Cambridge University Press, 2006.Description: xiii, 210 p. : ill. ; 25 cmISBN:
  • 9780521031967
  • 0521031966
Subject(s): DDC classification:
  • 621.36701519538   22
Contents:
1. Introduction -- 2. Statistical linear models -- 3. Line detection -- 4. Edge detection -- 5. Object detection -- 6. Image segmentation -- 7. Radial masks in line and edge detection -- 8. Performance analysis -- 9. Some approaches to image restoration.
Summary: A key problem in practical image processing is the detection of specific features in a noisy image. Analysis of variance (ANOVA) techniques can be very effective in such situations, and this book gives a detailed account of the use of ANOVA in statistical image processing. The book begins by describing the statistical representation of images in the various ANOVA models. The authors present a number of computationally efficient algorithms and techniques to deal with such problems as line, edge, and object detection, as well as image restoration and enhancement. By describing the basic principles of these techniques, and showing their use in specific situations, the book will facilitate the design of new algorithms for particular applications. It will be of great interest to graduate students and engineers in the field of image processing and pattern recognition.
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Item type Current library Call number Copy number Status Date due Barcode
Books Books Main library General Stacks 621.36701519538 / KU.A 2006 (Browse shelf(Opens below)) 1 Available 008310

1. Introduction -- 2. Statistical linear models -- 3. Line detection -- 4. Edge detection -- 5. Object detection -- 6. Image segmentation -- 7. Radial masks in line and edge detection -- 8. Performance analysis -- 9. Some approaches to image restoration.

Includes bibliographical references (p. 197-201) and index.

A key problem in practical image processing is the detection of specific features in a noisy image. Analysis of variance (ANOVA) techniques can be very effective in such situations, and this book gives a detailed account of the use of ANOVA in statistical image processing. The book begins by describing the statistical representation of images in the various ANOVA models. The authors present a number of computationally efficient algorithms and techniques to deal with such problems as line, edge, and object detection, as well as image restoration and enhancement. By describing the basic principles of these techniques, and showing their use in specific situations, the book will facilitate the design of new algorithms for particular applications. It will be of great interest to graduate students and engineers in the field of image processing and pattern recognition.

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