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Auteur Xiangchao Meng |
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An integrated framework for the spatio–temporal–spectral fusion of remote sensing images / Huanfeng Shen in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)
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Titre : An integrated framework for the spatio–temporal–spectral fusion of remote sensing images Type de document : Article/Communication Auteurs : Huanfeng Shen, Auteur ; Xiangchao Meng, Auteur ; Liangpei Zhang, Auteur Année de publication : 2016 Article en page(s) : pp 7135 - 7148 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme de fusion
[Termes IGN] données spatiotemporelles
[Termes IGN] fusion d'images
[Termes IGN] fusion de données multisource
[Termes IGN] image spectraleRésumé : (Auteur) Remote sensing satellite sensors feature a tradeoff between the spatial, temporal, and spectral resolutions. In this paper, we propose an integrated framework for the spatio-temporal-spectral fusion of remote sensing images. There are two main advantages of the proposed integrated fusion framework: it can accomplish different kinds of fusion tasks, such as multiview spatial fusion, spatio-spectral fusion, and spatio-temporal fusion, based on a single unified model, and it can achieve the integrated fusion of multisource observations to obtain high spatio-temporal-spectral resolution images, without limitations on the number of remote sensing sensors. The proposed integrated fusion framework was comprehensively tested and verified in a variety of image fusion experiments. In the experiments, a number of different remote sensing satellites were utilized, including IKONOS, the Enhanced Thematic Mapper Plus (ETM+), the Moderate Resolution Imaging Spectroradiometer (MODIS), the Hyperspectral Digital Imagery Collection Experiment (HYDICE), and Système Pour l' Observation de la Terre-5 (SPOT-5). The experimental results confirm the effectiveness of the proposed method. Numéro de notice : A2016-926 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2596290 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2596290 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83332
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 12 (December 2016) . - pp 7135 - 7148[article]