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Multivariate Image Processing

Multivariate Image Processing

Jocelyn Chanussot, Christophe Collet, Kacem Chehdi

ISBN: 978-1-848-21139-1

Dec 2009, Wiley-ISTE

464 pages

Select type: Hardcover

In Stock

$182.00

Description

Multivariate imagery is now a very common tool in numerous applications, ranging from satellite remote sensing and astrophysics to biomedical imagery, monitoring of the environment or industrial inspection. Multivariate must be understood in th emost general way: color and multispectral imaging, but also multimodal, multisource or multitemporal imagery. In all the cases, the multivariate image corresponds to a set of standard grey level images.

The availability of the additional diversity, be it spectral temporal and s.o., provides an invaluable source of information, enabling to consider a wide range of new applications. However, in order to address these applications, theoretical developments are required in terms of signal and image processing, or, more generally speaking, information processing. As a matter of fact, most of the standard algorithms designed for grey level images do not generalize easily to multidimensional spaces and some specific derivations are required.

This book aims at presenting the most recent advances in signal and image processing for the analysis of multivariate data. It should be helpful for electrical engineers, PhD students and researcher working in the field of signal processing, but also for any engineer dealing with some specific application where multidimensional data are processed.

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Optimisation in Signal and Image Processing (Hardcover $206.95)

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"A most welcome addition to the publishers' series on Digital Signal and Image Processing, this handsome book of fourteen chapters has perforce to be highly selective in its choice of subject matter. It is a welcome addition to the studies on the subject of multivariate image processing. All chapters measure up to this reviewer's expectations. This book aims at presenting the most recent advances in signal and image processing for the analysis of multivariate data. It should be helpful for electrical engineers, students at higher levels, and researchers working in the field of signal processing, and extremely ideal for any engineer dealing with a specific application where multidimensional data are processed." (Current Engineering Practice, 26 October 2010)