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On diverse noises in hyperspectral unmixing / Chunzhi Li in IEEE Transactions on geoscience and remote sensing, vol 53 n° 10 (October 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 10 (October 2015) . - pp 5388 - 5402 Titre : On diverse noises in hyperspectral unmixing Type de document : Article/Communication Auteurs : Chunzhi Li, Auteur ; Xiaohua Chen, Auteur ; Yunliang Jiang, Auteur Année de publication : 2015 Article en page(s) : pp 5388 - 5402 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse des mélanges spectraux [Termes IGN] bruit (théorie du signal) [Termes IGN] erreur aléatoire [Termes IGN] factorisation de matrice non-négative [Termes IGN] filtrage du bruit [Termes IGN] image hyperspectrale Résumé : (Auteur) Traditional spectral unmixing methods are usually based on the linear mixture model (LMM) or nonlinear mixture model (NLMM), in which only the additive noise is considered. However, in hyperspectral applications, the additive, multiplicative, and mixed noises play important roles. In this paper, we propose an antinoise model for hyperspectral unmixing. In the antinoise model, all the additive, multiplicative and mixed noises are addressed. To deal with the problems faced by LMM or NLMM and to tackle the antinoise model, an antinoise model based hyperspectral unmixing method is presented, where block coordinate descent is employed to solve an approximated L0 norm constraint, then a nonnegative matrix factorization (NMF) method is presented, which is based on the bounded Itakura-Saito divergence. The experimental results on both synthetic and real hyperspectral data sets demonstrate the efficacy of the proposed model and the corresponding method. Numéro de notice : A2015-751 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2421993 Date de publication en ligne : 01/05/2015 En ligne : https://doi.org/10.1109/TGRS.2015.2421993 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78739 [article]

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