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Hyperspectral unmixing based on mixtures of Dirichlet components / J. Nascimento in IEEE Transactions on geoscience and remote sensing, vol 50 n° 3 (March 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 3 (March 2012) . - pp 863 - 878 Titre : Hyperspectral unmixing based on mixtures of Dirichlet components Type de document : Article/Communication Auteurs : J. Nascimento, Auteur ; José Bioucas-Dias, Auteur Année de publication : 2012 Article en page(s) : pp 863 - 878 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse des mélanges spectraux [Termes IGN] classification non dirigée [Termes IGN] données lidar [Termes IGN] image hyperspectrale [Termes IGN] problème de Dirichlet Résumé : (Auteur) This paper introduces a new unsupervised hyperspectral unmixing method conceived to linear but highly mixed hyperspectral data sets, in which the simplex of minimum volume, usually estimated by the purely geometrically based algorithms, is far way from the true simplex associated with the endmembers. The proposed method, an extension of our previous studies, resorts to the statistical framework. The abundance fraction prior is a mixture of Dirichlet densities, thus automatically enforcing the constraints on the abundance fractions imposed by the acquisition process, namely, nonnegativity and sum-to-one. A cyclic minimization algorithm is developed where the following are observed: 1) The number of Dirichlet modes is inferred based on the minimum description length principle; 2) a generalized expectation maximization algorithm is derived to infer the model parameters; and 3) a sequence of augmented Lagrangian-based optimizations is used to compute the signatures of the endmembers. Experiments on simulated and real data are presented to show the effectiveness of the proposed algorithm in unmixing problems beyond the reach of the geometrically based state-of-the-art competitors. Numéro de notice : A2012-100 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2163941 En ligne : https://doi.org/10.1109/TGRS.2011.2163941 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31548 [article]

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