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

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 imag...

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Hauptverfasser: Réfrégier, Phillipe (VerfasserIn), Goudail, François (VerfasserIn)
Format: Elektronisch E-Book
Sprache:English
Veröffentlicht: New York, NY Springer US 2004
Ausgabe:1st ed. 2004
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Zusammenfassung: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
Beschreibung:1 Online-Ressource (XIII, 254 p. 93 illus)
ISBN:9781441988553
DOI:10.1007/978-1-4419-8855-3

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