Real-Time Progressive Hyperspectral Image Processing: Endmember Finding and Anomaly Detection

✍ Scribed by Chein-I Chang (auth.)

• Publisher: Springer-Verlag New York
• Year: 2016
• Tongue: English
• Leaves: 629
• Edition: 1
• Category: Library

✦ Synopsis

The book covers the most crucial parts of real-time hyperspectral image processing: causality and real-time capability. Recently, two new concepts of real time hyperspectral image processing, Progressive HyperSpectral Imaging (PHSI) and Recursive HyperSpectral Imaging (RHSI). Both of these can be used to design algorithms and also form an integral part of real time hyperpsectral image processing. This book focuses on progressive nature in algorithms on their real-time and causal processing implementation in two major applications, endmember finding and anomaly detection, both of which are fundamental tasks in hyperspectral imaging but generally not encountered in multispectral imaging. This book is written to particularly address PHSI in real time processing, while a book, Recursive Hyperspectral Sample and Band Processing: Algorithm Architecture and Implementation (Springer 2016) can be considered as its companion book.

✦ Table of Contents

Front Matter....Pages i-xxiii
Overview and Introduction....Pages 1-33
Front Matter....Pages 35-35
Linear Spectral Mixture Analysis....Pages 37-73
Finding Endmembers in Hyperspectral Imagery....Pages 75-103
Linear Spectral Unmixing With Three Criteria, Least Squares Error, Simplex Volume and Orthogonal Projection....Pages 105-129
Hyperspectral Target Detection....Pages 131-172
Front Matter....Pages 173-174
Fully Geometric-Constrained Sequential Endmember Finding: Simplex Volume Analysis-Based N-FINDR....Pages 175-242
Partially Geometric-Constrained Sequential Endmember Finding: Convex Cone Volume Analysis....Pages 243-272
Geometric-Unconstrained Sequential Endmember Finding: Orthogonal Projection Analysis....Pages 273-289
Fully Abundance-Constrained Sequential Endmember Finding: Linear Spectral Mixture Analysis....Pages 291-322
Front Matter....Pages 323-323
Fully Geometric-Constrained Progressive Endmember Finding: Growing Simplex Volume Analysis....Pages 325-360
Partially Geometric-Constrained Progressive Endmember Finding: Growing Convex Cone Volume Analysis....Pages 361-387
Geometric-Unconstrained Progressive Endmember Finding: Orthogonal Projection Analysis....Pages 389-412
Endmember-Finding Algorithms: Comparative Studies and Analyses....Pages 413-467
Front Matter....Pages 469-470
Anomaly Detection Characterization....Pages 471-493
Anomaly Discrimination and Categorization....Pages 495-519
Anomaly Detection and Background Suppression....Pages 521-545
Multiple Window Anomaly Detection....Pages 547-576
Anomaly Detection Using Causal Sliding Windows....Pages 577-595
Conclusions....Pages 597-605
Erratum to: Real-Time Progressive Hyperspectral Image Processing....Pages E1-E1
Back Matter....Pages 607-623

✦ Subjects

Signal, Image and Speech Processing; Image Processing and Computer Vision; Pattern Recognition; Biometrics