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

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

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Book Description
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.

Statistical Image Processing Techniques for Noisy Images: An Application-Oriented Approach,Phillipe Réfrégier,François Goudail,Springer,030647865X,Data Processing - Optical Data Processing,Image processing,Imaging Systems,Physics,Programming - Algorithms,Science,Science/Mathematics,Statistical methods,Technology & Industrial Arts,Communications engineering / telecommunications,Computers / Computer Graphics / General

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