Category: Conference Papers
Context-based endmember detection for hyperspectral imagery
August 10, 2009Abstract: An endmember detection algorithm that simultaneously partitions an input data set into distinct contexts, estimates endmembers, number of endmembers, and abundances for each partition is presented. In contrast to previous endmember detection algorithms based on the convex geometry model, this method is capable of describing non-convex sets of hyperspectral pixels. Endmembers are found for […]
Read more: Context-based endmember detection for hyperspectral imagery »Endmember detection using the dirichlet process
December 10, 2008Abstract: An endmember detection algorithm for hyperspectral imagery using the Dirichlet process to determine the number of endmembers in a hyperspectral image is described. This algorithm provides an estimate of endmember spectra, proportion maps, and the number of endmembers needed for a scene. Updates to the proportion vector for a pixel are sampled using the […]
Read more: Endmember detection using the dirichlet process »Sparsity promoting iterated constrained endmember detection with integrated band selection
July 1, 2007Abstract: An extension of the iterated constrained endmembers (ICE) that incorporates sparsity promoting priors to find the correct number of endmembers and simultaneously select informative spectral bands is presented. In addition to solving for endmembers and endmember fractional maps, this algorithm attempts to autonomously determine the number of endmembers required for a particular scene. The […]
Read more: Sparsity promoting iterated constrained endmember detection with integrated band selection »SPICE: a sparsity promoting iterated constrained endmember extraction algorithm with applications to landmine detection from hyperspectral imagery
April 26, 2007Abstract: An extension of the Iterated Constrained Endmembers (ICE) algorithm that incorporates sparsity promoting priors to find the correct number of endmembers is presented. In addition to solving for endmembers and endmember fractional maps, this algorithm attempts to autonomously determine the number of endmembers required for a particular scene. The number of endmembers is found […]
Read more: SPICE: a sparsity promoting iterated constrained endmember extraction algorithm with applications to landmine detection from hyperspectral imagery »Sensor fusion for airborne landmine detection
April 16, 2006Abstract: Sensor fusion has become a vital research area for mine detection because of the countermine community’s conclusion that no single sensor is capable of detecting mines at the necessary detection and false alarm rates over a wide variety of operating conditions. The U. S. Army Night Vision and Electronic Sensors Directorate (NVESD) evaluates sensors […]
Read more: Sensor fusion for airborne landmine detection »Multi-sensor and algorithm fusion with the choquet integral: applications to landmine detection
September 20, 2004Abstract: We discuss the application of Choquet integrals to multi-algorithm and multi-sensor fusion in landmine detection. Choquet integrals are defined. Specific classes of measures, the full and Sugeno measures, are described. Full measures are optimized via quadratic programming. A steepest descent algorithm for optimizing Sugeno measures is derived by applying implicit differentiation. Multiple detection algorithms […]
Read more: Multi-sensor and algorithm fusion with the choquet integral: applications to landmine detection »