Hyperspectral Data Exploitation Theory and

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.

Chein-I Chang, PHD, is Professor in the Department of Computer Sciences and Electrical Engineering at the University of Maryland, Baltimore County, where he directs the Remote Sensing Signal and Image Processing Laboratory. Dr. Chang is a Fellow of SPIE, the International Society for Optical Engineering, for his achievements in hyperspectral image processing. He is Associate Editor of the IEEE Transactions on Geoscience and Remote Sensing and the author of Hyperspectral Imaging: Techniques for Spectral Detection and Classification.

Overview
Tutorals
Hyperspectral Imaging Systems
Information-Processed Matched Filters for Hyperspectral Target Detection and Classification
Theory
An Optical Real-Time Adaptive Spectral Identification System (ORASIS)
Stochastic Mixture Modeling
Unmixing Hyperspectral Data: Independent and Dependent Component Analysis
Maximum Volume Transform For Endmember Spectra Determination
Hyperspectral Data Representation
Optimal Band Selection and Utility Evaluation for Spectral Systems
Feature Reduction for Classification Purpose
Semi-supervised Support Vector Machines for Classification of Hyperspectral Remote Sensing Images
Applications
Decision Fusion for Hyperspectral Classification
Morphological Hyperspectral Image Classification: A Parallel Processing Perspective
3D Wavelet-Based Compression of Hyperspectral Imagery
Table of Contents provided by Publisher. All Rights Reserved.

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Hyperspectral Data Exploitation Theory and Applications

Summary

Author Biography

Table of Contents

Supplemental Materials