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Novel fusion approach on automatic object extraction from spatial data: case study Worldview-2 and TOPO5000 / Umut Gunes Sefercik in Geocarto international, vol 33 n° 10 (October 2018)  

Public [article]  inGeocarto international > vol 33 n° 10 (October 2018) . - pp 1139 - 1154 Titre : Novel fusion approach on automatic object extraction from spatial data: case study Worldview-2 and TOPO5000 Type de document : Article/Communication Auteurs : Umut Gunes Sefercik, Auteur ; Serkan Karakis, Auteur ; Can Atalay, Auteur ; Ibrahim Yigit, Auteur ; Umit Gokmen, Auteur Année de publication : 2018 Article en page(s) : pp 1139 - 1154 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse d'image orientée objet [Termes IGN] détection d'objet [Termes IGN] détection du bâti [Termes IGN] extraction automatique [Termes IGN] extraction de traits caractéristiques [Termes IGN] extraction du réseau routier [Termes IGN] filtre de Wallis [Termes IGN] image numérique [Termes IGN] image Worldview [Termes IGN] modèle numérique de surface [Termes IGN] Turquie Résumé : (auteur) The automatic extraction of information content from remotely sensed data is always challenging. We suggest a novel fusion approach to improve the extraction of this information from mono-satellite images. A Worldview-2 (WV-2) pan-sharpened image and a 1/5000-scaled topographic vector map (TOPO5000) were used as the sample data. Firstly, the buildings and roads were manually extracted from WV-2 to point out the maximum extractable information content. Subsequently, object-based automatic extractions were performed. After achieving two-dimensional results, a normalized digital surface model (nDSM) was generated from the underlying digital aerial photos of TOPO5000, and the automatic extraction was repeated by fusion with the nDSM to include individual object heights as an additional band for classification. The contribution was tested by precision, completeness and overall quality. Novel fusion technique increased the success of automatic extraction by 7% for the number of buildings and by 23% for the length of roads. Numéro de notice : A2019-047 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2017.1353646 Date de publication en ligne : 27/07/2017 En ligne : https://doi.org/10.1080/10106049.2017.1353646 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92068 [article]

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