Analysis of variance in statistical image processing

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. 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. 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 the use of ANOVA in statistical image processing. By describing the basic principles of these techniques, and showing their use in specific situations, it will facilitate the design of new algorithms for particular applications, and will be invaluable to graduate students and engineers in the field of image processing and pattern recognition. In considering image processing problems, it is commonly required that certain types of basic patterns be extracted from a noisy and/or complex scene.

Detailed account of the techniques and applications of analysis of variance techniques in statistical image processing.

Recoge: Modelos estadísticos lineales; Detección de líneas; Segmentación de la imagen; Procedimentos estocásticos de aproximación