Tag: dirichlet process

Abstract: A semi-supervised Partial Membership Latent Dirichlet Allocation approach is developed for hyperspectral unmixing and endmember estimation while accounting for spectral variability and spatial information. Partial Membership Latent Dirichlet Allocation is an effective approach for spectral unmixing while representing spectral variability and leveraging spatial information. In this work, we extend Partial Membership Latent Dirichlet Allocation […]

Abstract: A Gibbs sampler for piece-wise convex hyperspectral unmixing and endmember detection is presented. The standard linear mixing model used for hyperspectral unmixing assumes that hyperspectral data reside in a single convex region. However, hyperspectral data is often non-convex. Furthermore, in standard unmixing methods, endmembers are generally represented as a single point in the high […]

Abstract: A new hyperspectral endmember detection method that represents endmembers as distributions, autonomously partitions the input data set into several convex regions, and simultaneously determines endmember distributions (EDs) and proportion values for each convex region is presented. Spectral unmixing methods that treat endmembers as distributions or hyperspectral images as piecewise convex data sets have not […]

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 […]