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Automatic geolocation correction of satellite imagery / Ozge C. Ozcanli in International journal of computer vision, vol 116 n° 3 (February 2016)  

Public [article]  inInternational journal of computer vision > vol 116 n° 3 (February 2016) . - pp 263–277 Titre : Automatic geolocation correction of satellite imagery Type de document : Article/Communication Auteurs : Ozge C. Ozcanli, Auteur ; Yi Dong, Auteur ; Joseph L. Mundy, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 263–277 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] alignement [Termes IGN] coordonnées géodésiques [Termes IGN] correction automatique [Termes IGN] géolocalisation [Termes IGN] géoréférencement [Termes IGN] image satellite [Termes IGN] modèle numérique de surface [Termes IGN] OpenStreetMap [Termes IGN] orthoimage [Termes IGN] reconstruction 3D [Termes IGN] réseau routier Résumé : (auteur) Modern satellites tag their images with geolocation information using GPS and star tracking systems. Depending on the quality of the geopositioning equipment, errors may range from a few meters to tens of meters on the ground. At the current state of art, there is no established method to automatically correct these errors limiting the large-scale joint utilization of cross-platform satellite images. In this paper, an automatic geolocation correction framework that corrects images from multiple satellites simultaneously is presented. As a result of the proposed correction process, all the images are effectively registered to the same absolute geodetic coordinate frame. The usability and the quality of the correction framework are demonstrated through a 3-D surface reconstruction application. The 3-D surface models given by original satellite geopositioning metadata, and the corrected metadata, are compared. The quality difference is measured through an entropy-based metric applied to the orthographic height maps given by the 3-D surface models. Measuring the absolute accuracy of the framework is harder due to lack of publicly available high-precision ground surveys. However, the geolocation of images of exemplar satellites from different parts of the globe are corrected, and the road networks given by OpenStreetMap are projected onto the images using original and corrected metadata to demonstrate the improved quality of alignment. Numéro de notice : A2016--146 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007%2Fs11263-015-0852-7 En ligne : https://doi.org/10.1007/s11263-015-0852-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85905 [article]

Geo-localization using volumetric representations of overhead imagery / Ozge C. Ozcanli in International journal of computer vision, vol 116 n° 3 (February 2016)  

Public [article]  inInternational journal of computer vision > vol 116 n° 3 (February 2016) . - pp 226 - 246 Titre : Geo-localization using volumetric representations of overhead imagery Type de document : Article/Communication Auteurs : Ozge C. Ozcanli, Auteur ; Yi Dong, Auteur ; Joseph L. Mundy, Auteur Année de publication : 2016 Article en page(s) : pp 226 - 246 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] appariement de formes [Termes IGN] attribut sémantique [Termes IGN] données lidar [Termes IGN] Etats-Unis [Termes IGN] géoréférencement [Termes IGN] image 2D [Termes IGN] image aérienne [Termes IGN] littoral [Termes IGN] prise de vue terrestre [Termes IGN] reconstruction 3D [Termes IGN] test de performance Résumé : (auteur) This paper addresses the problem of determining the location of a ground level image by using georeferenced overhead imagery. The input query image is assumed to be given with no metadata and the content of the image is to be matched to a priori constructed reference representations. The semantic breakdown of the content of the query image is provided through manual labeling; however, all processing involving the reference imagery and matching are fully automated. In this paper, a volumetric representation is proposed to fuse different modalities of overhead imagery and construct a 3D reference world. Attributes of this reference world such as orientation of the world surfaces, types of land cover, depth order of fronto-parallel surfaces are indexed and matched to the attributes of the surfaces manually marked on the query image. An exhaustive but highly parallelizable matching scheme is proposed and the performance is evaluated on a set of query images located in a coastal region in Eastern United States. The performance is compared to a baseline region reduction algorithm and to a landmark existence matcher that uses a 2D representation of the reference world. The proposed 3D geo-localization framework performs better than the 2D approach for 75 % of the query images. Numéro de notice : A2016--145 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007%2Fs11263-015-0850-9 En ligne : https://doi.org/10.1007/s11263-015-0850-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85904 [article]