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More About This Textbook
Overview
"This text covers key mathematical principles and algorithms for nonlinear filters used in image processing. Readers will gain an in-depth understanding of the underlying mathematical and filter design methodologies needed to construct and use nonlinear filters in a variety of applications.
The 11 chapters explore topics of contemporary interest as well as fundamentals drawn from nonlinear filtering's historical roots in mathematical morphology and digital signal processing. This book examines various filter options and the types of applications for which they are best suited. The presentation is rigorous, yet accessible to engineers with a solid background in mathematics."
"...readers will gain an in-depth understanding of the underlying mathematical & filter design methodologies needed to construct & utilize nonlinear filters in a variety of applications."
Editorial Reviews
Booknews
Written for mathematicians and engineers with a good mathematical background, 11 chapters cover key principles and algorithms for nonlinear filters. Topics of contemporary interest are discussed as well as fundamentals drawn from nonlinear filtering's historical roots in mathematical morphology and digital signaling processing. Topics include invariant signals of median and stack filters, applications of binary polynomial transforms, and connected operators. Annotation c. Book News, Inc., Portland, OR (booknews.com)Product Details
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Table of Contents
Preface.
Logical Image Operators (E. Dougherty & J. Barrera).
Computational Gray-Scale Operators (E. Dougherty & J. Barrera).
Translation-Invariant Set Operators (E. Dougherty).
Granulometric Filters (E. Dougherty & Y. Chen)
Easy Recipes for Morphological Filters (H. Heijmans).
Introduction to Connected Operators (H. Heijmans).
Representation and Optimization of Stack Filters (J. Astola & P. Kuosmanen).
Invariant Signals of Median and Stack Filters (J. Astola & P. Kuosmanen).
Binary Polynomial Transforms and Logical Correlation (K. Egiazarian, et al.).
Applications of Binary Polynomial Transforms (K. Egiazarian, et al.).
Random Sets in View of Image Filtering Applications (I. Molchanov).
Index.