Chein-I Chang: Hyperspectral Data Processing, Gebunden

Inhaltsangabe

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

Klappentext

A comprehensive reference on advanced hyperspectral imaging

Hyperspectral Data Processing: Algorithm Design and Analysis is a culmination of the research conducted in the Remote Sensing Signal and Image Processing Laboratory (RSSIPL) at the University of Maryland, Baltimore County. Specifically, it treats hyperspectral image processing and hyperspectral signal processing as separate subjects in two different categories. Most materials covered in this book can be used in conjunction with the author's first book, Hyperspectral Imaging: Techniques for Spectral Detection and Classification, without much overlap.

Many results in this book are either new or have not been explored, presented, or published in the public domain. These include various aspects of endmember extraction, unsupervised linear spectral mixture analysis, hyperspectral information compression, hyperspectral signal coding and characterization, as well as applications to conceal target detection, multispectral imaging, and magnetic resonance imaging.

Hyperspectral Data Processing contains eight major sections:

• Part I: provides fundamentals of hyperspectral data processing
• Part II: offers various algorithm designs for endmember extraction
• Parts III: derives theory for supervised linear spectral mixture analysis
• Part IV: designs unsupervised methods for hyperspectral image analysis
• Part V: explores new concepts on hyperspectral information compression
• Part VI & VII: develops techniques for hyperspectral signal coding and characterization
• Part VIII: presents applications in multispectral imaging and magnetic resonance imaging

Hyperspectral Data Processing compiles an algorithm compendium with MATLAB codes in an appendix to help readers implement many important algorithms developed in this book and write their own program codes without relying on software packages.

Hyperspectral Data Processing is a valuable reference for those who have been involved with hyperspectral imaging and its techniques, as well those who are new to the subject.

Sonstiges

Lieferung vom Verlag mit leichten Qualitätsmängeln möglich