Semi-Supervised Linear Spectral Unmixing Using a Hierarchical Bayesian Model for Hyperspectral Imagery

DOI10.1109/TSP.2008.917851zbMath1390.94156DBLPjournals/tsp/DobigeonTC08WikidataQ58830399 ScholiaQ58830399MaRDI QIDQ4568919

Jean-Yves Tourneret, Nicolas Dobigeon, Chein-I. Chang

Publication date: 27 June 2018

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

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Related Items (5)

Objective Bayesian analysis for the normal compositional model ⋮ A Bayesian approach to estimating linear mixtures with unknown covariance structure ⋮ Bayesian separation of spectral sources under non-negativity and full additivity constraints ⋮ An overview on linear unmixing of hyperspectral data ⋮ BEMMA: a hierarchical Bayesian end-member modeling analysis of sediment grain-size distributions

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