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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)
[article]
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 descripteurs IGN] appariement de graphes
[Termes descripteurs IGN] détection du bâti
[Termes descripteurs IGN] graphe
[Termes descripteurs IGN] image à résolution métrique
[Termes descripteurs IGN] image Ikonos
[Termes descripteurs IGN] image panchromatique
[Termes descripteurs IGN] milieu urbain
[Termes descripteurs IGN] SIFT (algorithme)
[Termes descripteurs IGN] sommet (mathématique)
[Termes descripteurs IGN] zone urbaineRésumé : (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 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29714
in IEEE Transactions on geoscience and remote sensing > vol 47 n° 4 (April 2009) . - pp 1156 - 1167[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-09041 RAB Revue Centre de documentation En réserve 3L Disponible 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)
[article]
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 descripteurs IGN] estimation de précision
[Termes descripteurs IGN] géoréférencement
[Termes descripteurs IGN] image à très haute résolution
[Termes descripteurs IGN] image Ikonos
[Termes descripteurs IGN] image ORBVIEW
[Termes descripteurs IGN] image Quickbird
[Termes descripteurs IGN] point d'appui
[Termes descripteurs IGN] point de vérificationRésumé : (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 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29715
in IEEE Transactions on geoscience and remote sensing > vol 47 n° 4 (April 2009) . - pp 1256 - 1261[article]Réservation
Réserver ce documentExemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 065-09041 RAB Revue Centre de documentation En réserve 3L Disponible