An investigation of likelihoods and priors for bayesian endmember estimation

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,… Read More

A comparison of deterministic and probabilistic approaches to endmember representation

Abstract: The piece-wise convex multiple model endmember detection algorithm (P-COMMEND) and the Piece-wise Convex End-member detection (PCE) algorithm autonomously estimate many sets of endmembers to represent a hyperspectral image. A piece-wise convex model with several sets of endmembers is more… Read More