Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral ImagerySPIE, 2007 - Computer algorithms |
Contents
A comparative study of linear and nonlinear anomaly detectors for hyperspectral imagery | 656504-1 |
Adaptive constrained signal detector for hyperspectral images 656504 | 656504-18 |
a comparison of methods using seasonal | 656506-1 |
Copyright | |
16 other sections not shown
Other editions - View all
Common terms and phrases
abundance AIRS Algorithms and Technologies angle anomaly detection applications approach area score atmospheric AVIRIS background bad pixel BRDF calibration change detection classification clutter computed corresponding covariance matrix data cube data set detection algorithms detector DIRSIG distribution eigenvectors emissivity endmembers Equation error estimate false alarms function Gaussian Geoscience and Remote global hyperspectral data hyperspectral image hyperspectral imagery IEEE independent component analysis infrared iterative kernel linear Mahalanobis distance mapping matched filter measured method MODTRAN Multispectral noise nonlinear optical optimal parameters performance pixels polarization Principal Component Analysis Proc processing projection radiance random reflectance region Remote Sensing resolution retrieval ROC curve samples scene scintillometer selection sensor shown in Figure shows signal simulated solar spatial spectral bands spectrometer spectrum SPIE Vol statistics subspace surface target detection techniques Technologies for Multispectral temperature threshold transform Ultraspectral Imagery unmixing vector wavelength