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Auteur Qing Cheng |
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Cloud removal for remotely sensed images by similar pixel replacement guided with a spatio-temporal MRF model / Qing Cheng in ISPRS Journal of photogrammetry and remote sensing, vol 92 (June 2014)
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Titre : Cloud removal for remotely sensed images by similar pixel replacement guided with a spatio-temporal MRF model Type de document : Article/Communication Auteurs : Qing Cheng, Auteur ; Huanfeng Shen, Auteur ; Liangpei Zhang, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 54 - 68 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] champ aléatoire de Markov
[Termes IGN] correction automatique
[Termes IGN] correction d'image
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Landsat
[Termes IGN] image multitemporelle
[Termes IGN] modèle conceptuel de données spatio-temporelles
[Termes IGN] nuage
[Termes IGN] pixel
[Termes IGN] température de surfaceRésumé : (Auteur) Cloud cover is generally present in remotely sensed images, which limits the potential of the images for ground information extraction. Therefore, removing the clouds and recovering the ground information for the cloud-contaminated images is often necessary in many applications. In this paper, an effective method based on similar pixel replacement is developed to solve this task. A missing pixel is filled using an appropriate similar pixel within the remaining region of the target image. A multitemporal image is used as the guidance to locate the similar pixels. A pixel-offset based spatio-temporal Markov random fields (MRF) global function is built to find the most suitable similar pixel. The proposed method was tested on MODIS and Landsat images and their land surface temperature products, and the experiments verify that the proposed method can achieve highly accurate results and is effective at dealing with the obvious atmospheric and seasonal differences between multitemporal images. Numéro de notice : A2014-289 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.02.015 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.02.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33192
in ISPRS Journal of photogrammetry and remote sensing > vol 92 (June 2014) . - pp 54 - 68[article]Exemplaires(1)
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