Bayesian Estimation of Linear Mixtures Using the Normal Compositional Model. Application to Hyperspectral Imagery

DOI10.1109/TIP.2010.2042993zbMath1373.62324OpenAlexW2097211423WikidataQ51715269 ScholiaQ51715269MaRDI QIDQ5366364

Olivier Eches, Nicolas Dobigeon, C. Mailhes, Jean-Yves Tourneret

Publication date: 9 October 2017

Published in: IEEE Transactions on Image Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1109/tip.2010.2042993

Mathematics Subject Classification ID

Bayesian inference (62F15) Image analysis in multivariate analysis (62H35) Monte Carlo methods (65C05)

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Objective Bayesian analysis for the normal compositional model ⋮ A Bayesian approach to estimating linear mixtures with unknown covariance structure ⋮ Using a Bayesian hierarchical linear mixing model to estimate botanical mixtures ⋮ Bayesian learning via neural Schrödinger-Föllmer flows

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