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Affiner la recherche Interroger des sources externesFusion of hyperspectral and VHR multispectral image classifications in urban α–areas / Alexandre Hervieu in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol III-3 (July 2016)
Titre : Fusion of hyperspectral and VHR multispectral image classifications in urban α–areas Type de document : Article/Communication Auteurs : Alexandre Hervieu Année de publication : 2016 Projets : HYEP / Weber, Christiane Article en page(s) : pp 457 - 464 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] fusion d'images
[Termes IGN] image hyperspectrale
[Termes IGN] image multibande
[Termes IGN] méthode de réduction d'énergie
[Termes IGN] occupation du sol
[Termes IGN] optimisation (mathématiques)
[Termes IGN] zone urbaineRésumé : (auteur) An energetical approach is proposed for classification decision fusion in urban areas using multispectral and hyperspectral imagery at distinct spatial resolutions. Hyperspectral data provides a great ability to discriminate land-cover classes while multispectral data,usually at higher spatial resolution, makes possible a more accurate spatial delineation of the classes. Hence, the aim here is to achieve the most accurate classification maps by taking advantage of both data sources at the decision level: spectral properties of the hyperspectral data and the geometrical resolution of multispectral images. More specifically, the proposed method takes into account probability class membership maps in order to improve the classification fusion process. Such probability maps are available using standard classification techniques such as Random Forests or Support Vector Machines. Classification probability maps are integrated into an energy framework where minimization of a given energy leads to better classification maps. The energy is minimized using a graph-cut method called quadratic pseudo-boolean optimization (QPBO) with α-expansion. A first model is proposed that gives satisfactory results in terms of classification results and visual interpretation. This model is compared to a standard Potts models adapted to the considered problem. Finally, the model is enhanced by integrating the spatial contrast observed in the data source of higher spatial resolution (i.e., the multispectral image). Obtained results using the proposed energetical decision fusion process are shown on two urban multispectral/hyperspectral datasets. 2-3% improvement is noticed with respect to a Potts formulation and 3-8% compared to a single hyperspectral-based classification. Numéro de notice : A2016-826 Affiliation des auteurs : LASTIG MATIS (2012-2019) Autre URL associée : vers HAL Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-III-3-457-2016 Date de publication en ligne : 06/06/2016 En ligne : http://dx.doi.org/10.5194/isprs-annals-III-3-457-2016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82697
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol III-3 (July 2016) . - pp 457 - 464[article]Documents numériques
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Fusion of hyperspectral and VHR ... - pdf éditeurAdobe Acrobat PDF
Titre : Forest stand segmentation using airborne lidar data and very high resolution multispectral imagery Type de document : Article/Communication Auteurs : Clément Dechesne Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2016 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 41-B3 Projets : 1-Pas de projet / Weber, Christiane Conférence : ISPRS 2016, Commission 3, 23th international congress 12/07/2016 19/07/2016 Prague République tchèque ISPRS OA Archives Commission 3 Importance : pp 207 - 214 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] algorithme Graph-Cut
[Termes IGN] classification dirigée
[Termes IGN] détection d'arbres
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image à très haute résolution
[Termes IGN] image multibande
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] semis de pointsRésumé : (auteur) Forest stands are the basic units for forest inventory and mapping. Stands are large forested areas (e.g., ≥ 2 ha) of homogeneous tree species composition. The accurate delineation of forest stands is usually performed by visual analysis of human operators on very high resolution (VHR) optical images. This work is highly time consuming and should be automated for scalability purposes. In this paper, a method based on the fusion of airborne laser scanning data (or lidar) and very high resolution multispectral imagery for automatic forest stand delineation and forest land-cover database update is proposed. The multispectral images give access to the tree species whereas 3D lidar point clouds provide geometric information on the trees. Therefore, multi-modal features are computed, both at pixel and object levels. The objects are individual trees extracted from lidar data. A supervised classification is performed at the object level on the computed features in order to coarsely discriminate the existing tree species in the area of interest. The analysis at tree level is particularly relevant since it significantly improves the tree species classification. A probability map is generated through the tree species classification and inserted with the pixel-based features map in an energetical framework. The proposed energy is then minimized using a standard graph-cut method (namely QPBO with α-expansion) in order to produce a segmentation map with a controlled level of details. Comparison with an existing forest land cover database shows that our method provides satisfactory results both in terms of stand labelling and delineation (matching ranges between 94% and 99%). Numéro de notice : C2016-040 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : FORET/IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/isprs-archives-XLI-B3-207-2016 Date de publication en ligne : 09/06/2016 En ligne : https://doi.org/10.5194/isprs-archives-XLI-B3-207-2016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91852 Documents numériques
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Forest stand segmentation ... - pdf éditeurAdobe Acrobat PDF
Titre : Road marking extraction using a model&data-driven RJ-MCMC Type de document : Article/Communication Auteurs : Alexandre Hervieu Année de publication : 2015 Conférence : ISPRS 2015, PIA 2015 - HRIGI 2015 Joint ISPRS conference 25/03/2015 27/03/2015 Munich Allemagne ISPRS OA Annals Article en page(s) : pp 47 - 54 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] espace image
[Termes IGN] méthode de Monte-Carlo par chaînes de Markov
[Termes IGN] orthoimage
[Termes IGN] projection orthogonale
[Termes IGN] signalisation routièreMots-clés libres : reversible-jump Markov chain Monte Carlo Résumé : (auteur) We propose an integrated bottom-up/top-down approach to road-marking extraction from image space. It is based on energy minimization using marked point processes. A generic road marking object model enable us to define universal energy functions that handle various types of road-marking objects (dashed-lines, arrows, characters, etc.). A RJ-MCMC sampler coupled with a simulated annealing is applied to find the configuration corresponding to the minimum of the proposed energy. We used input data measurements to guide the sampler process (data driven RJ-MCMC). The approach is enhanced with a model-driven kernel using preprocessed autocorrelation and inter-correlation of road-marking templates, in order to resolve type and transformation ambiguities. The method is generic and can be applied to detect road-markings in any orthogonal view produced from optical sensors or laser scanners from aerial or terrestrial platforms. We show the results an ortho-image computed from ground-based laser scanning. Numéro de notice : A2015-758 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprsannals-II-3-W4-47-2015 Date de publication en ligne : 11/05/2015 En ligne : http://dx.doi.org/10.5194/isprsannals-II-3-W4-47-2015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78754
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol II-3 W4 (March 2015) . - pp 47 - 54[article]Documents numériques
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Road marking extractionAdobe Acrobat PDF
Titre : Semi-automatic road/pavement modeling using mobile laser scanning Type de document : Article/Communication Auteurs : Alexandre Hervieu Année de publication : 2013 Projets : 1-Pas de projet / Weber, Christiane Conférence : CMRT 2013, City Models, Roads and Traffic 12/11/2013 13/11/2013 Antalya Turquie OA ISPRS Annals Article en page(s) : pp 31 - 36 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] chaussée
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] modèle numérique
[Termes IGN] précision centimétriqueRésumé : (auteur) Scene analysis, in urban environments, deals with street modeling and understanding. A street mainly consists of roadways, pavements (i.e., walking areas), facades, still and moving obstacles. In this paper, we investigate the surface modeling of roadways and pavements using LIDAR data acquired by a mobile laser scanning (MLS) system. First, road border detection is considered. A system recognizing curbs and curb ramps while reconstructing the missing information in case of occlusion is presented. A user interface scheme is also described, providing an effective tool for semi-automatic processing of large amount of data. Then, based upon road edge information, a process that reconstructs surfaces of roads and pavements has been developed, providing a centimetric precision while reconstructing missing information. This system hence provides an important knowledge of the street, that may open perspectives in various domains such as path planning or road maintenance. Numéro de notice : A2013-794 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprsannals-II-3-W3-31-2013 Date de publication en ligne : 08/10/2013 En ligne : http://dx.doi.org/10.5194/isprsannals-II-3-W3-31-2013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80400
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol II-3 W3 (November 2013) . - pp 31 - 36[article]
Titre : Road side detection and reconstruction using Lidar sensor Type de document : Article/Communication Auteurs : Alexandre Hervieu Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : June 2013 Projets : 2-Pas d'info accessible - article non ouvert / Weber, Christiane Conférence : IV 2013, IEEE Intelligent Vehicles Symposium 23/06/2013 26/06/2013 Gold Coast City Australie Proceedings IEEE Importance : pp 1247 - 1252 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] détection de contours
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] filtre de Kalman
[Termes IGN] reconstruction 3D
[Termes IGN] route
[Termes IGN] trottoirRésumé : (auteur) Road edge localization is key knowledge for automatic road modeling and hence, in the field of autonomous vehicles. In this paper, we investigate the case of road border detection using LIDAR data. The aim is to propose a system recognizing curbs and curb ramps and to reconstruct the missing information in case of occlusion. A prediction/estimation process (inspired by Kalman filter models) has been analyzed. The map of angle deviation to ground normal is considered as a feature set, helping to characterize efficiently curbs while curb ramps and occluded curbs have been handled with the proposed model. Such a method may be used for both road map modeling and driver-assistance systems. A user interface scheme has also been described, providing an effective tool for semi-automatic processing of a large amount of data. Numéro de notice : C2013-042 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IVS.2013.6629637 Date de publication en ligne : 15/10/2013 En ligne : http://dx.doi.org/10.1109/IVS.2013.6629637 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80223 Documents numériques
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Road side detection (poster)Adobe Acrobat PDF
https://www.linkedin.com/in/alexandre-hervieu-81ba42b0/