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Robust approach for urban road surface extraction using mobile laser scanning 3D point clouds / Abdul Nurunnabi (2022)  

Public Titre : Robust approach for urban road surface extraction using mobile laser scanning 3D point clouds Type de document : Article/Communication Auteurs : Abdul Nurunnabi, Auteur ; Felix Norman Teferle, Auteur ; Roderik Lindenbergh, Auteur ; J. Li, Auteur ; Sisi Zlatanova, Auteur Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2022 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 43-B1 Conférence : ISPRS 2022, Commission 1, 24th ISPRS international congress, Imaging today, foreseeing tomorrow 06/06/2022 11/06/2022 Nice France OA ISPRS Archives Importance : pp 59 - 66 Note générale : bibliographie This study is supported by the Project 2019-05-030-24, SOLSTICE - Programme Fonds Européen de Développment Régional (FEDER)/Ministère de l’Economie of the G. D. of Luxembourg Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] extraction de couche [Termes IGN] méthode robuste [Termes IGN] navigation autonome [Termes IGN] régression [Termes IGN] réseau routier [Termes IGN] sécurité routière [Termes IGN] semis de points [Termes IGN] véhicule sans pilote Résumé : (auteur) Road surface extraction is crucial for 3D city analysis. Mobile laser scanning (MLS) is the most appropriate data acquisition system for the road environment because of its efficient vehicle-based on-road scanning opportunity. Many methods are available for road pavement, curb and roadside way extraction. Most of them use classical approaches that do not mitigate problems caused by the presence of noise and outliers. In practice, however, laser scanning point clouds are not free from noise and outliers, and it is apparent that the presence of a very small portion of outliers and noise can produce unreliable and non-robust results. A road surface usually consists of three key parts: road pavement, curb and roadside way. This paper investigates the problem of road surface extraction in the presence of noise and outliers, and proposes a robust algorithm for road pavement, curb, road divider/islands, and roadside way extraction using MLS point clouds. The proposed algorithm employs robust statistical approaches to remove the consequences of the presence of noise and outliers. It consists of five sequential steps for road ground and non-ground surface separation, and road related components determination. Demonstration on two different MLS data sets shows that the new algorithm is efficient for road surface extraction and for classifying road pavement, curb, road divider/island and roadside way. The success can be rated in one experiment in this paper, where we extract curb points; the results achieve 97.28%, 100% and 0.986 of precision, recall and Matthews correlation coefficient, respectively. Numéro de notice : C2022-019 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/isprs-archives-XLIII-B1-2022-59-2022 Date de publication en ligne : 30/05/2022 En ligne : http://dx.doi.org/10.5194/isprs-archives-XLIII-B1-2022-59-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100845

vol III-1 - July 2016 - [actes] XXIII ISPRS Congress, Commission I, 12–19 July 2016, Prague, Czech Republic (Bulletin de ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences) / Lena Halounova  

Public [n° ou bulletin]  est un bulletin de ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences / International society for photogrammetry and remote sensing (1980 -) (2012 - )   Titre : vol III-1 - July 2016 - [actes] XXIII ISPRS Congress, Commission I, 12–19 July 2016, Prague, Czech Republic Type de document : Périodique Auteurs : Lena Halounova, Éditeur scientifique ; V. Safar, Éditeur scientifique ; Charles K. Toth, Éditeur scientifique ; Jakub Karas, Éditeur scientifique ; Huadong Guo, Éditeur scientifique ; Norbert Haala, Éditeur scientifique ; A. Habib, Éditeur scientifique ; Peter Reinartz, Éditeur scientifique ; X. Tang, Éditeur scientifique ; J. Li, Éditeur scientifique ; Costas Armenakis, Éditeur scientifique ; Görres Grenzdorffer, Éditeur scientifique ; P. Le Roux, Éditeur scientifique ; Stratos Stylianidis, Éditeur scientifique ; Reinhard Blasi, Éditeur scientifique ; M. Menard, Éditeur scientifique ; H. Dufourmount, Éditeur scientifique ; Z. Li, Éditeur scientifique Congrès : ISPRS 2016, 23th international congress (12 - 19 juillet 2016; Prague, République tchèque), Auteur Année de publication : 2016 Langues : Français (fre) Numéro de notice : sans Affiliation des auteurs : non IGN Nature : Numéro de périodique En ligne : http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/III-1/index.html Format de la ressource électronique : URL sommaire Permalink : https://documentation.ensg.eu/index.php?lvl=bulletin_display&id=27483 [n° ou bulletin]

Contient

• Hybrid online mobile laser scanner calibration through image alignment by mutual information / Mourad Miled in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol III-1 (July 2016)  
• Accuracy Validation of Large-scale Block Adjustment without Control of ZY3 Images over China / Yang Bo in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol III-1 (July 2016)  
• Refined satellite image orientation in the free open-source photogrammetric tools Apero/MicMac / Ewelina Rupnik in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol III-1 (July 2016)    

Generalized composite kernel framework for hyperspectral image classification / J. Li in IEEE Transactions on geoscience and remote sensing, vol 51 n° 9 (September 2013)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 51 n° 9 (September 2013) . - pp 4816 - 4829 Titre : Generalized composite kernel framework for hyperspectral image classification Type de document : Article/Communication Auteurs : J. Li, Auteur ; Prashanth Reddy Marpu, Auteur ; Antonio Plaza, Auteur ; José M. Bioucas-Dias, Auteur ; et al., Auteur Année de publication : 2013 Conférence : MicroRad 2012, 12th specialist meeting on microwave radiometry and remote sensing applications 05/03/2012 09/03/2012 Rome Italie Proceedings IEEE Article en page(s) : pp 4816 - 4829 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification dirigée [Termes IGN] données localisées [Termes IGN] image AVIRIS [Termes IGN] image hyperspectrale [Termes IGN] image ROSIS [Termes IGN] méthode fondée sur le noyau [Termes IGN] régression logistique [Termes IGN] séparateur à vaste marge Résumé : (Auteur) This paper presents a new framework for the development of generalized composite kernel machines for hyperspectral image classification. We construct a new family of generalized composite kernels which exhibit great flexibility when combining the spectral and the spatial information contained in the hyperspectral data, without any weight parameters. The classifier adopted in this work is the multinomial logistic regression, and the spatial information is modeled from extended multiattribute profiles. In order to illustrate the good performance of the proposed framework, support vector machines are also used for evaluation purposes. Our experimental results with real hyperspectral images collected by the National Aeronautics and Space Administration Jet Propulsion Laboratory's Airborne Visible/Infrared Imaging Spectrometer and the Reflective Optics Spectrographic Imaging System indicate that the proposed framework leads to state-of-the-art classification performance in complex analysis scenarios. Numéro de notice : A2013-536 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2230268 En ligne : https://doi.org/10.1109/TGRS.2012.2230268 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32673 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-2013091	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Automated delineation of individual tree crowns from lidar data by multi-scale analysis and segmentation / L. Jing in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 12 (December 2012)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 78 n° 12 (December 2012) . - pp 1275 - 1284 Titre : Automated delineation of individual tree crowns from lidar data by multi-scale analysis and segmentation Type de document : Article/Communication Auteurs : L. Jing, Auteur ; B. Hu, Auteur ; J. Li, Auteur ; T. Noland, Auteur Année de publication : 2012 Article en page(s) : pp 1275 - 1284 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse multiéchelle [Termes IGN] arbre (flore) [Termes IGN] détection automatique [Termes IGN] détection de contours [Termes IGN] données lidar [Termes IGN] segmentation d'image Résumé : (Auteur) A canopy height model (chm) derived from lidar data can be segmented to obtain individual tree crowns. However, branches, tree crowns, and tree clusters usually have similar shapes and overlapping sizes. This causes current individual tree crown delineation methods for CHMs to work less effectively on closed canopy deciduous or mixed wood forests consisting of various-sized tree crowns. Based on mult-scale analysis and segmentation, an innovative tree crown delineation method was developed in this study. In this method, the scale levels of target tree crowns are first morphologically determined; the CHM is filtered at the multiple scale levels; and local maxima within each filtered CHM are taken as markers to segment the original chm using the marker-controlled watershed method. After tree crown segments are selected from the multiple resulting segmentation maps and integrated together, a complete tree crown map is generated. In an experiment on natural forests in Ontario, Canada, the proposed method yielded crown maps having a good consistency with manual and visual interpretation. For instance, when compared to a manually delineated forest map, the automated method correctly delineated about 69 percent, 65 percent, and 73 percent of the tree crowns from plots of closed canopy coniferous, deciduous, and mixed wood forests, respectively. Numéro de notice : A2012-645 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.78.11.1275 En ligne : https://doi.org/10.14358/PERS.78.11.1275 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32091 [article]

Edge-guided multiscale segmentation of satellite multispectral imagery / J. Chen in IEEE Transactions on geoscience and remote sensing, vol 50 n° 11 Tome 1 (November 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 11 Tome 1 (November 2012) . - pp 4513 - 4520 Titre : Edge-guided multiscale segmentation of satellite multispectral imagery Type de document : Article/Communication Auteurs : J. Chen, Auteur ; J. Li, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 4513 - 4520 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse d'image numérique [Termes IGN] contour [Termes IGN] détection de contours [Termes IGN] filtre de Canny [Termes IGN] image multibande [Termes IGN] littoral [Termes IGN] segmentation d'image Résumé : (Auteur) This paper presents a new approach to multiscale segmentation of satellite multispectral imagery using edge information. The Canny edge detector is applied to perform multispectral edge detection. The detected edge features are then utilized in a multiscale segmentation loop, and the merge procedure for adjacent image objects is controlled by a separability criterion that combines edge information with segmentation scale. The significance of the edge is measured by adjacent partitioned regions to perform edge assessment. The present method is based on a half-partition structure, which is composed of three steps: single edge detection, separated pixel grouping, and significant feature calculation. The spectral distance of the half-partitions separated by the edge is calculated, compared, and integrated into the edge information. The results show that the proposed approach works well on satellite multispectral images of a coastal area. Numéro de notice : A2012-590 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2194502 Date de publication en ligne : 23/05/2012 En ligne : https://doi.org/10.1109/TGRS.2012.2194502 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32036 [article]

IconMap-based visualisation technique and its application in soil fertility analysis / X. Zhang in Cartographic journal (the), vol 49 n° 3 (August 2012)  

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Detecting water bodies on Radarsat imagery / G. Kuang in Geomatica, vol 65 n° 1 (March 2011)  

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Epipolar arrangement of satellite imagery by projection trajectory simplification / M. Wang in Photogrammetric record, vol 25 n° 132 (December 2010 - February 2011)  

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A two-step displacement correction algorithm for registration of lidar point clouds and aerial images without orientation parameters / H. Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 10 (October 2010)  

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An automatic mosaicking method for building facade texture mapping using a monocular close-range image sequence / Z. Kang in ISPRS Journal of photogrammetry and remote sensing, vol 65 n° 3 (May - June 2010)  

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Shoreline extraction from RADARSAT-2 intensity imagery using a narrow band level set segmentation approach / Y. Shu in Marine geodesy, vol 33 n° 2-3 (April - September 2010)  

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A DEM generalization by minor valley branch detection and grid filling / Tinghua Ai in ISPRS Journal of photogrammetry and remote sensing, vol 65 n° 2 (March - April 2010)  

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Automated extraction of buildings from Ikonos imagery by integrating spectral and spatial information / X. Wang in Geomatica, vol 63 n° 3 (September 2009)  

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Prediction and visualization of GPS multipath signals in urban areas using LiDAR Digital Surface Models and building footprints / J. Li in International journal of geographical information science IJGIS, vol 22 n°11-12 (november 2008)  

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Semi-automatic extraction of 3D lines using a scalable edge model and least-squares template matching / Xiangyun Hu in Geomatica, vol 62 n° 3 (September 2008)  

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