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Urban area and building detection using SIFT: Keypoints and Graph Theory / B. Simarcek in IEEE Transactions on geoscience and remote sensing, vol 47 n° 4 (April 2009)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 47 n° 4 (April 2009) . - pp 1156 - 1167 Titre : Urban area and building detection using SIFT: Keypoints and Graph Theory Type de document : Article/Communication Auteurs : B. Simarcek, Auteur ; C. Unsalan, Auteur Année de publication : 2009 Article en page(s) : pp 1156 - 1167 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] appariement de graphes [Termes IGN] détection du bâti [Termes IGN] graphe [Termes IGN] image à résolution métrique [Termes IGN] image Ikonos [Termes IGN] image panchromatique [Termes IGN] milieu urbain [Termes IGN] SIFT (algorithme) [Termes IGN] sommet (mathématique) [Termes IGN] zone urbaine Résumé : (Auteur) Very high resolution satellite images provide valuable information to researchers. Among these, urban-area boundaries and building locations play crucial roles. For a human expert, manually extracting this valuable information is tedious. One possible solution to extract this information is using automated techniques. Unfortunately, the solution is not straightforward if standard image processing and pattern recognition techniques are used. Therefore, to detect the urban area and buildings in satellite images, we propose the use of scale invariant feature transform (SIFT) and graph theoretical tools. SIFT keypoints are powerful in detecting objects under various imaging conditions. However, SIFT is not sufficient for detecting urban areas and buildings alone. Therefore, we formalize the problem in terms of graph theory. In forming the graph, we represent each keypoint as a vertex of the graph. The unary and binary relationships between these vertices (such as spatial distance and intensity values) lead to the edges of the graph. Based on this formalism, we extract the urban area using a novel multiple subgraph matching method. Then, we extract separate buildings in the urban area using a novel graph cut method. We form a diverse and representative test set using panchromatic 1-m-resolution Ikonos imagery. By extensive testings, we report very promising results on automatically detecting urban areas and buildings. Copyright IEEE Numéro de notice : A2009-084 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2008.2008440 En ligne : https://doi.org/10.1109/TGRS.2008.2008440 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29714 [article]

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Georeferencing accuracy assessment of High-Resolution satellite images using figure condition method / Hyseyin Topan in IEEE Transactions on geoscience and remote sensing, vol 47 n° 4 (April 2009)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 47 n° 4 (April 2009) . - pp 1256 - 1261 Titre : Georeferencing accuracy assessment of High-Resolution satellite images using figure condition method Type de document : Article/Communication Auteurs : Hyseyin Topan, Auteur ; H.S. Kutoglu, Auteur Année de publication : 2009 Article en page(s) : pp 1256 - 1261 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] estimation de précision [Termes IGN] géoréférencement [Termes IGN] image à très haute résolution [Termes IGN] image Ikonos [Termes IGN] image ORBVIEW [Termes IGN] image Quickbird [Termes IGN] point d'appui [Termes IGN] point de vérification Résumé : (Auteur) In the case of sensor-independent georeferencing, accuracy of the used model is commonly assessed by misfits separately obtained from ground control points and independent check points. However, applying only this approach has some disadvantages. This paper proposes using the figure condition method to support the common approach. Applying the figure condition process, a more rigorous analysis of accuracy for the used models can be conducted, and one can decide whether the used model is proper or not. In this contribution, a case study is carried out using affine and extended affine models for high-resolution IKONOS Geo, OrbView-3 Basic, and QuickBird OrthoReady Standard images. The results obtained are subjected to the analysis of figure condition. Copyright IEEE Numéro de notice : A2009-085 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2008.2008098 En ligne : https://doi.org/10.1109/TGRS.2008.2008098 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29715 [article]

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