Overview
Optical remote sensing relies on exploiting multispectral and hyper spectral imagery possessing high spatial and spectral resolutions respectively. These modalities, although useful for most remote sensing tasks, often present challenges that must be addressed for their effective exploitation. This book presents current state-of-the-art algorithms that address the following key challenges encountered in representation and analysis of such optical remotely sensed data. Challenges in pre-processing images, storing and representing high dimensional data, fusing different sensor modalities, pattern classification and target recognition, visualization of high dimensional imagery.
Full Product Details
Author: Saurabh Prasad ,
Lori M. Bruce ,
Jocelyn Chanussot
Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition: 2011 ed.
Volume: 3
Dimensions:
Width: 15.50cm
, Height: 2.50cm
, Length: 23.50cm
Weight: 0.693kg
ISBN: 9783642142116
ISBN 10: 3642142117
Pages: 344
Publication Date: 23 March 2011
Audience:
Professional and scholarly
,
Professional & Vocational
Format: Hardback
Publisher's Status: Active
Availability: In Print
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Reviews
From the reviews: This book is composed of contributions that address many of the contemporary problems faced when processing hyperspectral image data. As expected, there are chapters focussed on thematic mapping and classification, spectral un-mixing, morphology and compression ! . important to anyone interested in the state of kernel based methods in image analysis. ! It is very well written, makes very good use of examples and will be an important reference work for those working on un-mixing problems. (John Richards, IEEE Geoscience and Remote Sensing Society Newsletter, June, 2011)
From the reviews: This book is composed of contributions that address many of the contemporary problems faced when processing hyperspectral image data. As expected, there are chapters focussed on thematic mapping and classification, spectral un-mixing, morphology and compression ... . important to anyone interested in the state of kernel based methods in image analysis. ... It is very well written, makes very good use of examples and will be an important reference work for those working on un-mixing problems. (John Richards, IEEE Geoscience and Remote Sensing Society Newsletter, June, 2011) This excellent reference focuses on advances in signal processing and exploitation techniques for optical remote sensing with a collection of state-of-the art algorithms for hyperspectral and multispectral imaging technologies. It is intended for advanced users, particularly graduate students and image scientists specializing in the field of optical remote sensing. ... This cutting-edge publication includes a collection of images and graphics, processing technologies and parallel implementations with up-to-date references at the end of each chapter. (Axel Mainzer Koenig, Optics & Photonics News, July, 2012)
From the reviews: This book is composed of contributions that address many of the contemporary problems faced when processing hyperspectral image data. As expected, there are chapters focussed on thematic mapping and classification, spectral un-mixing, morphology and compression . important to anyone interested in the state of kernel based methods in image analysis. It is very well written, makes very good use of examples and will be an important reference work for those working on un-mixing problems. (John Richards, IEEE Geoscience and Remote Sensing Society Newsletter, June, 2011)
