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A stochastic framework for the identification of building rooftops using a single remote sensing image / A. Katartzis in IEEE Transactions on geoscience and remote sensing, vol 46 n° 1 (January 2008)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 46 n° 1 (January 2008) . - pp 259 - 271 Titre : A stochastic framework for the identification of building rooftops using a single remote sensing image Type de document : Article/Communication Auteurs : A. Katartzis, Auteur ; H. Sahli, Auteur Année de publication : 2008 Article en page(s) : pp 259 - 271 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] champ aléatoire de Markov [Termes IGN] détection de contours [Termes IGN] géométrie projective [Termes IGN] image aérienne [Termes IGN] image isolée [Termes IGN] modèle stochastique [Termes IGN] reconstruction 3D du bâti [Termes IGN] toit Résumé : (Auteur) The identification of building rooftops from a single image, without the use of auxiliary 3-D information like stereo pairs or digital elevation models, is a very challenging and difficult task in the area of remote sensing. The existing methodologies rarely tackle the problem of 3-D object identification, like buildings, from a purely stochastic viewpoint. Our approach is based on a stochastic image interpretation model, which combines both 2-D and 3-D contextual information of the imaged scene. Building rooftop hypotheses are extracted using a contour-based grouping hierarchy that emanates from the principles of perceptual organization. We use a Markov random field model to describe the dependencies between all available hypotheses with regard to a globally consistent interpretation. The hypothesis verification step is treated as a stochastic optimization process that operates on the whole grouping hierarchy to find the globally optimal configuration for the locally interacting grouping hypotheses, providing also an estimate of the height of each extracted rooftop. This paper describes the main principles of our method and presents building detection results on a set of synthetic and airborne images. Copyright IEEE Numéro de notice : A2008-045 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2007.904953 En ligne : https://doi.org/10.1109/TGRS.2007.904953 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29040 [article]

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