Mathematical Methods for Signal and Image Analysis and Representation (Hardcover, 2012)

Mathematical Methods for Signal and Image Analysis and Representation presents the mathematical methodology for generic image analysis tasks. In the context of this book an image may be any m-dimensional empirical signal living on an n-dimensional smooth manifold (typically, but not necessarily, a subset of spacetime). The existing literature on image methodology is rather scattered and often limited to either a deterministic or a statistical point of view. In contrast, this book brings together these seemingly different points of view in order to stress their conceptual relations and formal analogies. Furthermore, it does not focus on specific applications, although some are detailed for the sake of illustration, but on the methodological frameworks on which such applications are built, making it an ideal companion for those seeking a rigorous methodological basis for specific algorithms as well as for those interested in the fundamental methodology per se. Covering many topics at the forefront of current research, including anisotropic diffusion filtering of tensor fields, this book will be of particular interest to graduate and postgraduate students and researchers in the fields of computer vision, medical imaging and visual perception.

General

Imprint:	Springer London
Country of origin:	United Kingdom
Series:	Computational Imaging and Vision, 41
Release date:	2012
First published:	2012
Editors:	Luc Florack • Remco Duits • Geurt Jongbloed • Marie-Colette van Lieshout • Laurie Davies
Dimensions:	235 x 155 x 23mm (L x W x T)
Format:	Hardcover
Pages:	320
Edition:	2012
ISBN-13:	978-1-4471-2352-1
Categories:	Books > Science & Mathematics > Mathematics > Applied mathematics > General Books > Computing & IT > Applications of computing > Image processing > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General
LSN:	1-4471-2352-2
Barcode:	9781447123521

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