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.
Sprache
Verlagsort
Verlagsgruppe
Illustrationen
93
93 s/w Abbildungen
XIII, 254 p. 93 illus.
Dateigröße
ISBN-13
978-1-4419-8855-3 (9781441988553)
DOI
10.1007/978-1-4419-8855-3
Schweitzer Klassifikation
