Hyperspectral Data Exploitation: Theory and Applications

Copyright © 2007 John Wiley & Sons, Inc.

Hyperspectral Data Exploitation: Theory and Applications

Editor(s): Chein-I Chang

Published Online: 19 SEP 2006

Print ISBN: 9780471746973

Online ISBN: 9780470124628

DOI: 10.1002/0470124628

About this Book

Product Information

About The Product

Authored by a panel of experts in the field, this book focuses on hyperspectral image analysis, systems, and applications. With discussion of application-based projects and case studies, this professional reference will bring you up-to-date on this pervasive technology, wether you are working in the military and defense fields, or in remote sensing technology, geoscience, or agriculture.

Table of contents

    1. You have free access to this content
      Frontmatter (pages i–x)

    1. Chapter 1

      Overview (pages 1–16)

      Chein-I Chang

  3. Part I: Tutorials

    1. Chapter 2

      Hyperspectral Imaging Systems (pages 17–45)

      John P. Kerekes and John R. Schott

    2. Chapter 3

      Information-Processed Matched Filters for Hyperspectral Target Detection and Classification (pages 47–74)

      Chein-I Chang

  4. Part II: Theory

    1. Chapter 4

      An Optical Real-Time Adaptive Spectral Identification System (ORASIS) (pages 75–106)

      Jeffrey H. Bowles and David B. Gillis

    2. Chapter 5

      Stochastic Mixture Modeling (pages 107–148)

      Michael T. Eismann and David W. J. Stein

    3. Chapter 6

      Unmixing Hyperspectral Data: Independent and Dependent Component Analysis (pages 149–177)

      Jose M. P. Nascimento and Jose M. B. Dias

    4. Chapter 7

      Maximum Volume Transform for Endmember Spectra Determination (pages 179–203)

      Michael E. Winter

    5. Chapter 8

      Hyperspectral Data Representation (pages 205–225)

      Xiuping Jia and John A. Richards

    6. Chapter 9

      Optimal Band Selection and Utility Evaluation for Spectral Systems (pages 227–243)

      Sylvia S. Shen

    7. Chapter 10

      Feature Reduction for Classification Purpose (pages 245–274)

      Sebastiano B. Serpico, Gabriele Moser and Andrea F. Cattoni

    8. Chapter 11

      Semisupervised Support Vector Machines for Classification of Hyperspectral Remote Sensing Images (pages 275–311)

      Lorenzo Bruzzone, Mingmin Chi and Mattia Marconcini

  5. Part III: Applications

    1. Chapter 12

      Decision Fusion for Hyperspectral Classification (pages 313–351)

      Mathieu Fauvel, Jocelyn Chanussot and Jon Atli Benediktsson

    2. Chapter 13

      Morphological Hyperspectral Image Classification: A Parallel Processing Perspective (pages 353–378)

      Antonio J. Plaza

    3. Chapter 14

      Three-Dimensional Wavelet-Based Compression of Hyperspectral Imagery (pages 379–407)

      James E. Fowler and Justin T. Rucker

    1. You have free access to this content
      Index (pages 409–430)

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