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Use Markov random fields for automatic cloud-shadow detection on high resolution / Sylvie Le Hégarat-Mascle in ISPRS Journal of photogrammetry and remote sensing, vol 64 n° 4 (July - August 2009)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 64 n° 4 (July - August 2009) . - pp 351 - 366 Titre : Use Markov random fields for automatic cloud-shadow detection on high resolution Type de document : Article/Communication Auteurs : Sylvie Le Hégarat-Mascle, Auteur ; Cyrille André, Auteur Année de publication : 2009 Article en page(s) : pp 351 - 366 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] champ aléatoire de Markov [Termes IGN] connexité (graphes) [Termes IGN] détection automatique [Termes IGN] graphe [Termes IGN] image optique [Termes IGN] nuage [Termes IGN] ombre [Termes IGN] pixel [Termes IGN] processus ponctuel marqué Résumé : (Auteur) In this study, we propose an automatic detection algorithm for cloud/shadow on remote sensing optical images. It is based on physical properties of clouds and shadows, namely for a cloud and its associated shadow: both are connex objects of similar shape and area, and they are related by their relative locations. We show that these properties can be formalized using Markov Random Field (MRF) framework at two levels: one MRF over the pixel graph for connexity modelling, and one MRF over the graph of objects (clouds and shadows) for their relationship modelling. Then, we show that, practically, having performed an image pre-processing step (channel inter-calibration) specific to cloud detection, the local optimization of the proposed MRF models leads to a rather simple image processing algorithm involving only six parameters. Using a 39 image database, performance is shown and discussed, in particular in comparison with the Marked Point Process approach. Numéro de notice : A2009-294 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2008.12.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2008.12.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29924 [article]

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