TY - CONF T1 - A hybrid algorithm for subpixel detection in hyperspectral imagery T2 - Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International Y1 - 2004 A1 - Broadwater, J. A1 - Meth, R. A1 - Chellapa, Rama KW - alarm KW - algorithm;abundance KW - algorithm;Fully KW - algorithm;hybrid KW - algorithm;statistical KW - AMSD;Adaptive KW - analysis;structured KW - approximations;maximum KW - backgrounds;subpixel KW - constrained KW - detection;alarm KW - detection;target KW - Detector;FCLS KW - detector;hyperspectral KW - estimation; KW - estimation;emittance KW - identification;adaptive KW - imagery;reflectance KW - least KW - likelihood KW - Matched KW - matching;least KW - processing;geophysical KW - rate;generalized KW - ratio KW - signal KW - signatures;spectral KW - spectra;false KW - spectra;spectral KW - squares KW - subspace KW - systems;geophysical KW - techniques;image KW - tests;hybrid KW - unmixing AB - Numerous subpixel detection algorithms utilizing structured backgrounds have been developed over the past few years. These range from detection schemes based on spectral unmixing to generalized likelihood ratio tests. Spectral unmixing algorithms such as the Fully Constrained Least Squares (FCLS) algorithm have the advantage of physically modeling the interactions of spectral signatures based on reflectance/emittance spectroscopy. Generalized likelihood ratio tests like the Adaptive Matched Subspace Detector (AMSD) have the advantage of identifying targets that are statistically different from the background. Therefore, a hybrid detector based on both AMSD and FCLS was developed to take advantage of each detector's strengths. Results demonstrate that the hybrid detector achieved the lowest false alarm rates while also producing meaningful abundance estimates JA - Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International VL - 3 M3 - 10.1109/IGARSS.2004.1370633 ER -