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A feature-preserving point cloud denoising algorithm for LiDAR-derived DEM construction / Chuanfa Chen in Survey review, Vol 53 n° 377 (February 2021)  

Public [article]  inSurvey review > Vol 53 n° 377 (February 2021) . - pp146 - 157 Titre : A feature-preserving point cloud denoising algorithm for LiDAR-derived DEM construction Type de document : Article/Communication Auteurs : Chuanfa Chen, Auteur ; Yuan Gao, Auteur ; Yanyan Li, Auteur Année de publication : 2021 Article en page(s) : pp146 - 157 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] algorithme de filtrage [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] filtrage de points [Termes IGN] filtrage du bruit [Termes IGN] interpolation [Termes IGN] modèle numérique de surface [Termes IGN] semis de points Résumé : (auteur) To attenuate positional errors of LiDAR-derived datasets for constructing digital elevation models (DEMs), a feature-preserving point denoising algorithm (F-PDA) is developed in this paper. F-PDA includes three main steps: surface normal estimation, normal filtering and point position update. Numerical tests with two simulated surfaces indicate that F-PDA is always more accurate than kriging and natural neighbour. Furthermore, F-PDA has a high effectiveness of preserving feature lines. Real-world examples of interpolating LiDAR samples demonstrate that F-PDA can best retain both prominent and subtle terrain features, while faithfully removing errors in mountainous and flat regions. Moreover, it outperforms some well-known interpolation methods. Numéro de notice : A2021-235 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2019.1704562u Date de publication en ligne : 23/12/2019 En ligne : https://doi.org/10.1080/00396265.2019.1704562u Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97242 [article]

Robust interpolation of DEMs from lidar-derived elevation data / Chuanfa Chen in IEEE Transactions on geoscience and remote sensing, vol 56 n° 2 (February 2018)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 56 n° 2 (February 2018) . - pp 1059 - 1068 Titre : Robust interpolation of DEMs from lidar-derived elevation data Type de document : Article/Communication Auteurs : Chuanfa Chen, Auteur ; Yanyan Li, Auteur ; Na Zhao, Auteur ; Changqing Yan, Auteur Année de publication : 2018 Article en page(s) : pp 1059 - 1068 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] fonction spline [Termes IGN] interpolation [Termes IGN] méthode robuste [Termes IGN] modèle numérique de surface Résumé : (Auteur) Light detection and ranging (lidar)-derived elevation data are commonly subjected to outliers due to the boundaries of occlusions, physical imperfections of sensors, and surface reflectance. Outliers have a serious negative effect on the accuracy of digital elevation models (DEMs). To decrease the impact of outliers on DEM construction, we propose a robust interpolation algorithm of multiquadric (MQ) based on a regularized least absolute deviation (LAD) technique. The objective function of the proposed method includes a regularization-based smoothing term and an LAD-based fitting term, respectively, used to smooth noisy samples and resist the influence of outliers. To solve the objective function of the proposed method, we develop a simple scheme based on the split-Bregman iteration algorithm. Results from simulated data sets indicate that when sample points are noisy or contaminated by outliers, the proposed method is more accurate than the classical MQ and two recently developed robust algorithms of MQ for surface modeling. Real-world examples of interpolating 1 private and 11 publicly available airborne lidar-derived data sets demonstrate that the proposed method averagely produces better results than two promising interpolation methods including regularized spline with tension (RST) and gridded data-based robust thin plate spline (RTPS). Specifically, the image of RTPS is too smooth to retain terrain details. Although RST can keep subtle terrain features, it is distorted by some misclassified object points (i.e., pseudooutliers). The proposed method obtains a good tradeoff between resisting the effect of outliers and preserving terrain features. Overall, the proposed method can be considered as an alternative for interpolating lidar-derived data sets potentially including outliers. Numéro de notice : A2018-193 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2758795 Date de publication en ligne : 17/10/2017 En ligne : https://doi.org/10.1109/TGRS.2017.2758795 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89858 [article]

An adaptive method of non-stationary variogram modeling for DEM error surface simulation / Chuanfa Chen in Transactions in GIS, vol 16 n° 6 (December 2012)  

Public [article]  inTransactions in GIS > vol 16 n° 6 (December 2012) . - pp 885 - 899 Titre : An adaptive method of non-stationary variogram modeling for DEM error surface simulation Type de document : Article/Communication Auteurs : Chuanfa Chen, Auteur ; Yanyan Li, Auteur Année de publication : 2012 Article en page(s) : pp 885 - 899 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] diagramme de Voronoï [Termes IGN] erreur [Termes IGN] modèle numérique de terrain [Termes IGN] Setchouan (Chine) [Termes IGN] simulation de surface [Termes IGN] variogramme Résumé : (Auteur) Geostatistical characterization of local DEM error is usually based on the assumption of a stationary variogram model which requires the mean and variance to be finite and constant in the area under investigation. However, in practice this assumption is appropriate only in a restricted spatial location, where the local experimental variograms vary slowly. Therefore, an adaptive method is developed in this article to model non-stationary variograms, for which the estimator and the indicator for characterization of spatial variation are a Voronoi map and the standard deviation of mean values displayed in the Voronoi map, respectively. For the adaptive method, the global domain is divided into different meshes with various sizes according to the variability of local variograms. The adaptive method of non-stationary variogram modeling is applied to simulating error surfaces of a LiDAR derived DEM located in Sichuan province, China. Results indicate that the locally adaptive variogram model is more accurate than the global one for capturing the characterization of spatial variation in DEM errors. The adaptive model can be considered as an alternative approach to modeling non-stationary variograms for DEM error surface simulation. Numéro de notice : A2012-619 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/j.1467-9671.2012.01326.x En ligne : https://doi.org/10.1111/j.1467-9671.2012.01326.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32065 [article]