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Hyperspectral image noise reduction based on rank-1 tensor decomposition / Xian Guoa in ISPRS Journal of photogrammetry and remote sensing, vol 83 (September 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 83 (September 2013) . - pp 50 - 63 Titre : Hyperspectral image noise reduction based on rank-1 tensor decomposition Type de document : Article/Communication Auteurs : Xian Guoa, Auteur ; Xian Guo, Auteur ; Xin Huang, Auteur ; Liangpei Zhanga, Auteur ; Lefei Zhang, Auteur Année de publication : 2013 Article en page(s) : pp 50 - 63 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] calcul tensoriel [Termes IGN] décomposition spatiale [Termes IGN] filtrage du bruit [Termes IGN] image hyperspectrale [Termes IGN] tenseur [Termes IGN] valeur propre [Termes IGN] voxel Résumé : (Auteur) In this study, a novel noise reduction algorithm for hyperspectral imagery (HSI) is proposed based on high-order rank-1 tensor decomposition. The hyperspectral data cube is considered as a three-order tensor that is able to jointly treat both the spatial and spectral modes. Subsequently, the rank-1 tensor decomposition (R1TD) algorithm is applied to the tensor data, which takes into account both the spatial and spectral information of the hyperspectral data cube. A noise-reduced hyperspectral image is then obtained by combining the rank-1 tensors using an eigenvalue intensity sorting and reconstruction technique. Compared with the existing noise reduction methods such as the conventional channel-by-channel approaches and the recently developed multidimensional filter, the spatial–spectral adaptive total variation filter, experiments with both synthetic noisy data and real HSI data reveal that the proposed R1TD algorithm significantly improves the HSI data quality in terms of both visual inspection and image quality indices. The subsequent image classification results further validate the effectiveness of the proposed HSI noise reduction algorithm. Numéro de notice : A2013-488 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.06.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.06.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32626 [article]

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