Tag: unmixing

Abstract: An endmember detection and spectral unmixing algorithm that uses both spatial and spectral information is presented. This method, Spatial Piece-wise Convex Multiple Model Endmember Detection (Spatial P-COMMEND), autonomously estimates multiple sets of endmembers and performs spectral unmixing for input hyperspectral data. Spatial P-COMMEND does not restrict the estimated endmembers to define a single convex […]

Abstract: A hyperspectral endmember detection and spectral unmixing algorithm based on an l1 norm factorization of the input hyperspectral data is developed and compared to a method based on l2 norm factorization. Both algorithms, the L1-Endmembers algorithm based on the l1 norm and the SPICE algorithm based on the l2 norm, simultaneously and autonomously estimate […]

Abstract: 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 […]

Abstract: 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 […]

Abstract: Four methods of endmember detection and spectral unmixing are described. The methods determine endmembers and perform spectral unmixing while simultaneously determining the number of endmembers, representing endmembers as distributions, partitioning the input data set into several convex regions, or performing hyperspectral band selection. Few endmember detection algorithms estimate the number of endmembers in addition […]

Abstract: This letter presents a simultaneous band selection and endmember detection algorithm for hyperspectral imagery. This algorithm is an extension of the sparsity promoting iterated constrained endmember (SPICE) algorithm. The extension adds spectral band weights and a sparsity promoting prior to the SPICE objective function to provide integrated band selection. In addition to solving for […]

Abstract: 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 […]

Abstract: An extension of the iterated constrained endmember (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 that are required for a particular scene. The number of endmembers is […]

Abstract: 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 […]