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OverviewStatistical 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. Full Product DetailsAuthor: Phillipe Réfrégier , François GoudailPublisher: Springer-Verlag New York Inc. Imprint: Springer-Verlag New York Inc. Edition: 2004 ed. Dimensions: Width: 15.50cm , Height: 1.40cm , Length: 23.50cm Weight: 0.421kg ISBN: 9781461346920ISBN 10: 1461346924 Pages: 254 Publication Date: 17 November 2013 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand ![]() We will order this item for you from a manufactured on demand supplier. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |