Analysis of variance in statistical image processing / Ludwik Kurz and M. Hafed Benteftifa.
Material type: TextPublisher: Cambridge : Cambridge University Press, 1997Description: 1 online resource (xiii, 210 pages) : digital, PDF file(s)Content type:- text
- computer
- online resource
- 9780511530166 (ebook)
- 621.36/7/01519538 20
- TA1637 .K87 1997
Title from publisher's bibliographic system (viewed on 05 Oct 2015).
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.
A key problem in practical image processing is that of detecting certain 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. A number of computationally efficient algorithms and techniques are then presented, 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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