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New approaches for estimating local point density and its impact on lidar data segmentation / Z. Lari in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 2 (February 2013)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 79 n° 2 (February 2013) . - pp 195 - 207 Titre : New approaches for estimating local point density and its impact on lidar data segmentation Type de document : Article/Communication Auteurs : Z. Lari, Auteur ; A. Habib, Auteur Année de publication : 2013 Article en page(s) : pp 195 - 207 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] contrôle qualité [Termes IGN] densité des points [Termes IGN] données lidar [Termes IGN] filtrage du bruit [Termes IGN] qualité des données [Termes IGN] réflexion (rayonnement) [Termes IGN] segmentation [Termes IGN] semis de points [Termes IGN] traitement de données Résumé : (Auteur) Lidar systems have been proven as a cost-effective tool for the collection of high density and accurate point cloud over physical surfaces. The collected point cloud does not exhibit homogenous point distribution due to the characteristics of the scanning system and/or the physical properties of the scanned surfaces. In order to effectively process the lidar point clouds, local point density variations should be quantified and taken into account for the definition of processing parameters. In this paper, new approaches are presented for the estimation of local point density indices while considering the 3D relationship among lidar points, the physical properties of the reflecting surfaces, and the noise level in the datasets collected by different laser scanners. The impact of considering the estimated local point density variations on the quality of lidar data segmentation results is then investigated by performing a quality control procedure. Quantitative evaluation of segmentation results highlights the efficacy of utilizing the estimated local point density indices for the derivation of more accurate segmentation. Numéro de notice : A2013-079 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.79.2.195 En ligne : https://doi.org/10.14358/PERS.79.2.195 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32217 [article]