Real-Time Progressive Hyperspectral Image Processing

PRELIMINARIES.- Overview and Introduction.- Virtual Dimensionality for Hyperspectral Imagery.- Linear Spectra: Mixture Analysis.- Endmember Extraction.- SEQUENTIAL ENDMEMBER EXTRACTION.- Abundance-Unconstrained Sequential Endmember Extraction: Orthogonal Projection.- Fully Abundance-Constrained Sequential Endmember Extraction: Simplex Volume Analysis.- Partially Abundance Non-Negativity-Constrained Sequential Endmember Extraction: Convex Cone Volume Analysis.- Fully Abundance-Constrained Sequential Linear Spectral Mixture Analysis.- PROGRESSIVE ENDMEMBER EXTRACTION.- Abundance-Unconstrained Progressive Endmember Extraction Orthogonal Projection.- Fully Abundance-Constrained Progressive Endmember Extraction: Simplex Volume Analysis.- Partially Abundance Non-Negativity -Constrained Progressive Endmember Extraction: Convex Cone Volume Analysis.- Fully Abundance-Constrained Progressive Linear Spectral MixtureAnalysis.- PROGRESSIVE UNSUPERVISED TARGET DETECTION.- Anomaly Detection.- AdaptiveAnomaly Detection.- Window-Based Anomaly Detection.- Subpixel Target Detection and Classification.- PROGRESSIVE BAND PROCESSING.- Progressive Band Selection of LSMA.- Progressive Band Processing of Endmember Extraction.- Progressive Band Processing of Target Detection.- Progressive Band Processing of Signal Coding.- FIELD PROGRAMMABLE GATE ARRAYS (FPGA) DESIGN.- FPGA Design for PPI.- FPGA Design for N-Finder and SGA.- FPGA Design for Subpixel Detection.- FPGA Design for Orthogonal Subspace Projection (OSP).- Conclusions.