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Table of Contents
Overview and introduction
Linear spectral mixture analysis
Finding endmembers in hyperspectral imagery
Linear spectral unmixing with three criteria, least squares error, simplex volume and orthogonal projection
Hyperspectral target detection
Fully geometric-constrained sequential endmember finding: simplex volume analysis-based N-FINDR
Partially geometric-constrained sequential endmember finding: convex cone volume analysis
Geometric-unconstrained sequential endmember finding: orthogonal projection analysis
Fully abundance-constrained sequential endmember finding: linear spectral mixture analysis
Fully geometric-constrained progressive endmember finding: growing simplex volume analysis
Partially geometric-constrained progressive endmember finding: growing convex cone volume analysis
Geometric-unconstrained progressive endmember finding: orthogonal projection analysis
Endmember finding algorithms: comparative studies and analyses
Anomaly detection characterization
Anomaly discrimination and categorization
Anomaly detection and background suppression
Multiple window anomaly detection
Anomaly detection using causal sliding windows.
Linear spectral mixture analysis
Finding endmembers in hyperspectral imagery
Linear spectral unmixing with three criteria, least squares error, simplex volume and orthogonal projection
Hyperspectral target detection
Fully geometric-constrained sequential endmember finding: simplex volume analysis-based N-FINDR
Partially geometric-constrained sequential endmember finding: convex cone volume analysis
Geometric-unconstrained sequential endmember finding: orthogonal projection analysis
Fully abundance-constrained sequential endmember finding: linear spectral mixture analysis
Fully geometric-constrained progressive endmember finding: growing simplex volume analysis
Partially geometric-constrained progressive endmember finding: growing convex cone volume analysis
Geometric-unconstrained progressive endmember finding: orthogonal projection analysis
Endmember finding algorithms: comparative studies and analyses
Anomaly detection characterization
Anomaly discrimination and categorization
Anomaly detection and background suppression
Multiple window anomaly detection
Anomaly detection using causal sliding windows.