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Filtering airborne LiDAR data by embedding smoothness-constrained segmentation in progressive TIN densification / Jixian Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 81 (July 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 81 (July 2013) . - pp 44 - 59 Titre : Filtering airborne LiDAR data by embedding smoothness-constrained segmentation in progressive TIN densification Type de document : Article/Communication Auteurs : Jixian Zhang, Auteur ; Xiangguo Lin, Auteur Année de publication : 2013 Article en page(s) : pp 44 - 59 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] densification [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] filtrage du signal [Termes IGN] segmentation [Termes IGN] semis de points [Termes IGN] traitement automatique de données [Termes IGN] Triangulated Irregular Network Résumé : (Auteur) Progressive TIN densification (PTD) is one of the classic methods for filtering airborne LiDAR point clouds. However, it may fail to preserve ground measurements in areas with steep terrain. A method is proposed to improve the PTD using a point cloud segmentation method, namely segmentation using smoothness constraint (SUSC). The classic PTD has two core steps. The first is selecting seed points and constructing the initial TIN. The second is an iterative densification of the TIN. Our main improvement is embedding the SUSC between these two steps. Specifically, after selecting the lowest points in each grid cell as initial ground seed points, SUSC is employed to expand the set of ground seed points as many as possible, as this can identify more ground seed points for the subsequent densification of the TIN-based terrain model. Seven datasets of ISPRS Working Group III/3 are utilized to test our proposed algorithm and the classic PTD. Experimental results suggest that, compared with the PTD, the proposed method is capable of preserving discontinuities of landscapes and reducing the omission errors and total errors by approximately 10% and 6% respectively, which would significantly decrease the cost of the manual operation required for correcting the result in post-processing. Numéro de notice : A2013-388 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.04.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.04.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32526 [article]

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