Thursday 28 July 2011

Analysis of Variance in Statistical Image Processing

Analysis of Variance in Statistical Image Processing
Author: Ludwik Kurz
Edition:
Binding: Hardcover
ISBN: 0521581826



Analysis of Variance in Statistical Image Processing


A key problem in practical image processing is the detection of specific features in a noisy image. Get Analysis of Variance in Statistical Image Processing computer books for free.
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. Check Analysis of Variance in Statistical Image Processing our best computer books for 2013. All books are available in pdf format and downloadable from rapidshare, 4shared, and mediafire.

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Analysis of Variance in Statistical Image Processing Download


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 nalysis 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.

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