|  | Chang, Chein-I
Hyperspectral Data Processing
Algorithm Design and Analysis
 1. Auflage März 2013
169,- Euro
2013. 1164 Seiten, Hardcover
ISBN 978-0-471-69056-6 - John Wiley & Sons
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| Kurzbeschreibung
This book is intended to be a sequel to the author's previous work, Hyperspectral Imaging: Techniques for Spectral Detection and Classification. It is comprised of five major parts and covers a wealth of information, including: a discussion of OSP, FPGA designs for OSP and CEM, Kalman filter-based linear unmixing, least squares fully constrained linear mixture analysis, interference rejection for linear unmixing, signal-composed interference-annihilated theory, techniques for linear unmixing, spectral coding, and more.
Aus dem Inhalt
PREFACE xxiii
1 OVERVIEWAND INTRODUCTION 1
I: PRELIMINARIES 31
2 FUNDAMENTALS OF SUBSAMPLE AND MIXED SAMPLE ANALYSES 33
3 THREE-DIMENSIONAL RECEIVER OPERATING CHARACTERISTICS (3D ROC) ANALYSIS 63
4 DESIGN OF SYNTHETIC IMAGE EXPERIMENTS 101
5 VIRTUAL DIMENSIONALITY OF HYPERSPECTRAL DATA 124
6 DATA DIMENSIONALITY REDUCTION 168
II: ENDMEMBER EXTRACTION 201
7 SIMULTANEOUS ENDMEMBER EXTRACTION ALGORITHMS (SM-EEAs) 207
8 SEQUENTIAL ENDMEMBER EXTRACTION ALGORITHMS (SQ-EEAs) 241
(UNCLS-EEA) 249
9 INITIALIZATION-DRIVEN ENDMEMBER EXTRACTION ALGORITHMS (ID-EEAs) 265
10 RANDOM ENDMEMBER EXTRACTION ALGORITHMS (REEAs) 287
11 EXPLORATION ON RELATIONSHIPS AMONG ENDMEMBER EXTRACTION ALGORITHMS 316
III: SUPERVISED LINEAR HYPERSPECTRAL MIXTURE ANALYSIS 351
12 ORTHOGONAL SUBSPACE PROJECTION REVISITED 355
13 FISHER'S LINEAR SPECTRAL MIXTURE ANALYSIS 391
14 WEIGHTED ABUNDANCE-CONSTRAINED LINEAR SPECTRAL MIXTURE ANALYSIS 411
15 KERNEL-BASED LINEAR SPECTRAL MIXTURE ANALYSIS 434
IV: UNSUPERVISED HYPERSPECTRAL IMAGE ANALYSIS 465
16 HYPERSPECTRAL MEASURES 469
17 UNSUPERVISED LINEAR HYPERSPECTRAL MIXTURE ANALYSIS 483
18 PIXEL EXTRACTION AND INFORMATION 526
V: HYPERSPECTRAL INFORMATION COMPRESSION 541
19 EXPLOITATION-BASED HYPERSPECTRAL DATA COMPRESSION 545
20 PROGRESSIVE SPECTRAL DIMENSIONALITY PROCESS 581
21 PROGRESSIVE BAND DIMENSIONALITY PROCESS 613
22 DYNAMIC DIMENSIONALITYALLOCATION 664
23 PROGRESSIVE BAND SELECTION 683
VI: HYPERSPECTRAL SIGNAL CODING 717
24 BINARY CODING FOR SPECTRAL SIGNATURES 719
25 VECTOR CODING FOR HYPERSPECTRAL SIGNATURES 741
26 PROGRESSIVE CODING FOR SPECTRAL SIGNATURES 772
VII: HYPERSPECTRAL SIGNAL CHARACTERIZATION 797
27 VARIABLE-NUMBERVARIABLE-BAND SELECTION FOR HYPERSPECTRAL SIGNALS 799
28 KALMAN FILTER-BASED ESTIMATION FOR HYPERSPECTRAL SIGNALS 820
29 WAVELET REPRESENTATION FOR HYPERSPECTRAL SIGNALS 859
VIII: APPLICATIONS 877
30 APPLICATIONS OF TARGET DETECTION 879
31 NONLINEAR DIMENSIONALITY EXPANSION TO MULTISPECTRAL IMAGERY 897
32 MULTISPECTRAL MAGNETIC RESONANCE IMAGING 920
33 CONCLUSIONS 956
GLOSSARY 993
APPENDIX: ALGORITHM COMPENDIUM 997
REFERENCES 1052
INDEX 1071
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