000			02022cam a2200265 a 4500
008			100325s2006 nyua b 001 0 eng
020			_a9780521031967
020			_a0521031966
035			_a(Sirsi) u5620
040			_aEG-CaNU _c EG-CaNU _d EG-CaNU
042			_ancode
082	0	4	_a621.36701519538 _2 22
100	1		_aKurz, Ludwik _911156
245	1	0	_aAnalysis of variance in statistical image processing / _c Ludwik Kurz and M. Hafed Benteftifa.
260			_aCambridge ; New York : _b Cambridge University Press, _c 2006.
300			_axiii, 210 p. : _b ill. ; _c 25 cm.
505	0		_a1. 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.
504			_aIncludes bibliographical references (p. 197-201) and index.
520			_aA 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.
650		0	_aImage processing _x Statistical methods. _911157
650		0	_aAnalysis of variance. _911158
700			_aEnteftifa, M. Hafed _911159
920			_a0521581826 (hardback)
596			_a1
999			_c4627 _d4627