Statistical Image Processing Techniques for Noisy Images - An Application-Oriented Approach (Paperback, 2004 ed.)

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.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Release date:	April 2014
First published:	2004
Authors:	Phillipe Refregier • Francois Goudail
Dimensions:	235 x 155 x 19mm (L x W x T)
Format:	Paperback
Pages:	254
Edition:	2004 ed.
ISBN-13:	978-1-4613-4692-0
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Science & Mathematics > Physics > Optics (light) Books > Earth & environment > Geography > Cartography, geodesy & geographic information systems (GIS) > Geographical information systems (GIS) Books > Earth & environment > Geography > Cartography, geodesy & geographic information systems (GIS) > Remote sensing Books > Computing & IT > Applications of computing > Artificial intelligence > Computer vision Books > Computing & IT > Applications of computing > Image processing > General Promotions
LSN:	1-4613-4692-4
Barcode:	9781461346920

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