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Digital surface model generation from high resolution multi-view stereo satellite imagery / Ke Gong in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 5 (May 2019)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 5 (May 2019) . - pp 379 - 387 Titre : Digital surface model generation from high resolution multi-view stereo satellite imagery Type de document : Article/Communication Auteurs : Ke Gong, Auteur ; Dieter Fritsch, Auteur Année de publication : 2019 Article en page(s) : pp 379 - 387 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] angle de visée [Termes IGN] Argentine [Termes IGN] chaîne de traitement [Termes IGN] géométrie épipolaire [Termes IGN] image multitemporelle [Termes IGN] image Worldview [Termes IGN] modèle numérique de surface [Termes IGN] semis de points Résumé : (Auteur) Along with improvements to spatial resolution, multiple-view stereo satellite imagery has become a valuable datasource for digital surface model generation. In 2016, a public multi-view stereo benchmark of commercial satellite imag- ery was released by the John Hopkins University Applied Physics Laboratory, USA. Motivated by this well-organized benchmark, we propose a pipeline to process multi-view satellite imagery into digital surface models. Input images are selected based on view angles and capture dates. We apply the relative bias-compensated model for orientation, and then generate the epipolar image pairs. The images are matched by the modified tube-based SemiGlobal Matching method (tSGM). Within the triangulation step, very dense point clouds are produced, and are fused by a median filter to generate the Digital Surface Model (DSM). A comparison with the reference data shows that the fused DSM generated by our pipeline is accurate and robust. Numéro de notice : A2019-440 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.5.379 Date de publication en ligne : 01/05/2019 En ligne : https://doi.org/10.14358/PERS.85.5.379 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92771 [article]

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