An edition of Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data (2004)

Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data

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Cover of: Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data by Pramod K. Varshney, Pramod K. Varshney
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An edition of Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data (2004)

Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data

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The main objective of this book is to apprise the reader of the use of a number of tools and techniques for a variety of image processing tasks, namely Independent Component Analysis (ICA), Mutual Information (MI), Markov Random Field (MRF) Models and Support Vector Machines (SVM). Typical applications considered are feature extraction, image classification, image fusion and change detection. The book also treats a number of experimental examples based on a variety of remote sensors. The utility of the book will be highly appreciated by academicians and R & D professionals, who are involved in current research in the area of hyperspectral imaging, as well as by professional remote-sensing data users such as geologists, hydrologists, environmental scientists, civil engineers and computer scientists.

Publish Date
Publisher
Springer Berlin Heidelberg
Language
English
Pages
323

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Previews available in: English

Subjects

Computer engineering, Geography, Geographical information systems, Environmental toxicology, Image processing, digital techniques, Remote sensing, Photography

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Cover of: Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data
Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data
2004, Springer Berlin Heidelberg
electronic resource / in English
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Book Details

Table of Contents

Hyperspectral Sensors and Applications
Overview of Image Processing
Mutual Information: A Similarity Measure for Intensity Based Image Registration
Independent Component Analysis
Support Vector Machines
Markov Random Field Models
Applications: MI Based Registration of Multi-Sensor and Multi-Temporal Images
Feature Extraction from Hyperspectral Data Using ICA
Hyperspectral Classification using ICA Based Mixture Model
Support Vector Machines for Classification of Multi- and Hyperspectral Data
An MRF Model Based Approach for Sub-pixel Mapping from Hyperspectral Data
Image Change Detection and Fusion Using MRF Models.

Edition Notes

Online full text is restricted to subscribers.

Also available in print.

Mode of access: World Wide Web.

Published in
Berlin, Heidelberg

Classifications

Dewey Decimal Class
910.285
Library of Congress
GA1-1776, G1-922

The Physical Object

Format
[electronic resource] /
Pagination
1 online resource (xv, 323 p.)
Number of pages
323

ID Numbers

Open Library
OL27014590M
Internet Archive
advancedimagepro00vars
ISBN 10
3642060013, 3662056054
ISBN 13
9783642060014, 9783662056059
OCLC/WorldCat
851377090

Source records

Internet Archive item record
Better World Books record
Better World Books record

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History

Download catalog record: RDF / JSON / OPDS | Wikipedia citation
January 27, 2022 Edited by ImportBot import existing book
January 27, 2022 Edited by ImportBot import existing book
June 28, 2019 Created by MARC Bot Imported from Internet Archive item record