Statistical Image Processing Techniques for Noisy Images: An Application-Oriented Approach

Réfrégier, Phillipe; Goudail, François

Statistical Processing Techniques for Noisy Images presents a statistical framework to design algorithms for target detection, tracking, segmentation and classification (identification). Its main goal is to provide the reader with efficient tools for developing algorithms that solve his/her own image processing applications. In particular, such topics as hypothesis test-based detection, fast active contour segmentation and algorithm design for non-conventional imaging systems are comprehensively treated, from theoretical foundations to practical implementations. With a large number of illustrations and practical examples, this book serves as an excellent textbook or reference book for senior or graduate level courses on statistical signal/image processing, as well as a reference for researchers in related fields.

Details

Published by: Springer

Publication Date: 2013-11-17

Format: Paperback

ISBN-13: 9781461346920

DOI: 10.1007/978-1-4419-8855-3

Dimensions: 235cm x155cm

Pages: 254