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Titre : Contribution of band selection and fusion for hyperspectral classification Type de document : Article/Communication Auteurs : Nesrine Chehata , Auteur ; Arnaud Le Bris , Auteur ; Safa Najjar, Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2014 Conférence : WHISPERS 2014, 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing 24/06/2014 27/06/2014 Lausanne Suisse Proceedings IEEE Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] fusion d'images
[Termes IGN] image hyperspectraleRésumé : (auteur) For some specific land cover classification problems, it may be interesting to design superspectral camera systems with reduced numbers of bands (∼ 20) and optimized band widths. This paper assesses the contribution of band selection and band fusion processes separately and jointly for dimensionality reduction. The proposed approach is fully automatic and based on a wrapper feature selection using Random forest classifier and a similarity-based fusion process. While combining both processes, selection before fusion gave the best results, reducing by almost 91% the number of bands while keeping satisfying accuracies. Results are presented on Indian Pines, Salinas and Pavia Centre hyperspectral datasets. Numéro de notice : C2014-040 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/WHISPERS.2014.8077484 Date de publication en ligne : 26/10/2017 En ligne : https://doi.org/10.1109/WHISPERS.2014.8077484 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99582 Documents numériques
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Titre : Efficient fusion of multidimensional descriptors for image retrieval Type de document : Article/Communication Auteurs : Neelanjan Bhowmik , Auteur ; V. Ricardo Gonzalez, Auteur ; Valérie Gouet-Brunet , Auteur ; Helio Pedrini, Auteur ; Gabriel Bloch, Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2014 Projets : POEME / Da Silva, Jean-Claude Conférence : ICIP 2014, 21st IEEE International Conference on Image Processing 27/10/2014 30/10/2014 Paris France Proceedings IEEE Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse d'image orientée objet
[Termes IGN] analyse visuelle
[Termes IGN] banque d'images
[Termes IGN] base de données d'images
[Termes IGN] descripteur
[Termes IGN] état de l'art
[Termes IGN] fusion de données
[Termes IGN] index
[Termes IGN] mesure de similitude
[Termes IGN] recherche d'image basée sur le contenu
[Termes IGN] réductionRésumé : (auteur) Due to the large diversity of existing feature descriptors in content-based image retrieval, the image contents can be better represented by the joint use of several descriptors in order to explore their potentially complementary characteristics. This paper presents and discusses a strategy for fusion of the different multidimensional features involved, based on inverted multi-indices and dedicated to similarity search. Image descriptors are quantized separately and efficiently through dimension reduction techniques, before being combined in the inverted multi-indices. To exhibit its effectiveness, the proposal is evaluated on two datasets having different contents and sizes, facing several state-of-the-art approaches of image descriptor fusion. The obtained results reconfirm that the joint use of several descriptions improves similarity search, and show that our fusion proposal outperforms other solutions, while manipulating lower or similar volumes of features. Numéro de notice : C2014-033 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/ICIP.2014.7026166 Date de publication en ligne : 29/01/2015 En ligne : https://doi.org/10.1109/ICIP.2014.7026166 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92058 Documents numériques
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Efficient fusion of multidimensional ... - pdf auteurAdobe Acrobat PDF Identify important spectrum bands for classification using importances of wrapper selection applied to hyperspectral data / Arnaud Le Bris (2014)
Titre : Identify important spectrum bands for classification using importances of wrapper selection applied to hyperspectral data Type de document : Article/Communication Auteurs : Arnaud Le Bris , Auteur ; Nesrine Chehata , Auteur ; Xavier Briottet , Auteur ; Nicolas Paparoditis , Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2014 Conférence : IWCIM 2014, International Workshop on Computational Intelligence for Multimedia Understanding 01/11/2014 02/11/2014 Paris France Proceedings IEEE Importance : pp Note générale : bibliographie Langues : Anglais (eng) Résumé : (auteur) Intermediate results of two state-of-the-art wrapper feature selection approaches (GA and SFFS) applied to hyperspectral data sets were used to derive information about band importance for specific land cover classification problems. Several feature selection performance scores (classification accuracies, Bhattacharyya separability) were tested. The impact of the number of selected bands on classification accuracy was obtained thanks to SFFS, while a band importance measure was derived from intermediate sets of bands tested by GA. Such results are a first step toward the identification of the most suitable spectral bands to design superspectral camera systems dedicated to specific applications (e.g. classification of urban land cover and material maps). Numéro de notice : C2014-021 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IWCIM.2014.7008806 Date de publication en ligne : 15/01/2015 En ligne : http://dx.doi.org/10.1109/IWCIM.2014.7008806 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83403 Individual tree segmentation over large areas using airborne LiDAR point cloud and very high resolution optical imagery / Yuchu Qin (2014)
Titre : Individual tree segmentation over large areas using airborne LiDAR point cloud and very high resolution optical imagery Type de document : Article/Communication Auteurs : Yuchu Qin, Auteur ; António Ferraz , Auteur ; Clément Mallet , Auteur ; Corina Iovan , Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2014 Conférence : IGARSS 2014, International Geoscience And Remote Sensing Symposium 13/07/2014 18/07/2014 Québec Québec - Canada Proceedings IEEE Importance : pp 800 - 803 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] algorithme de décalage moyen
[Termes IGN] arbre (flore)
[Termes IGN] chaîne de traitement
[Termes IGN] détection d'arbres
[Termes IGN] diamètre des arbres
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] France (administrative)
[Termes IGN] image à très haute résolution
[Termes IGN] image optique
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] peuplement forestier
[Termes IGN] segmentation d'image
[Termes IGN] semis de points
[Termes IGN] Ventoux, MontRésumé : (auteur) Timely and accurate measurements of forest parameters are critical for ecosystem studies, sustainable forest resources management, monitoring and planning. This paper presents a processing chain for individual tree segmentation over large areas with airborne LiDAR 3D point cloud and very high resolution (VHR) optical imagery. The proposed processing chain consists of forest stand level delineation with optical imagery, individual tree segmentation with Canopy Height Model (CHM) derived from LiDAR point cloud, rough characterization of trees at forest stand level, and point clustering of individual tree with an Adaptive Mean Shift 3D (AMS3D) algorithm. The processing chain is developed with the expectation of supporting operational forest inventory at individual tree level. Experiment is conducted using LiDAR data acquired in Ventoux region, France. Results suggest that the proposed processing chain can be successfully adopted for individual tree characterization over large areas with different forest stands. Numéro de notice : C2014-025 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IGARSS.2014.6946545 Date de publication en ligne : 06/11/2014 En ligne : http://dx.doi.org/10.1109/IGARSS.2014.6946545 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92034 Documents numériques
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Individual tree segmentation ... - pdf auteurAdobe Acrobat PDF Large scale road network extraction in forested moutainous areas using airborne laser scanning data / António Ferraz (2014)
Titre : Large scale road network extraction in forested moutainous areas using airborne laser scanning data Type de document : Article/Communication Auteurs : António Ferraz , Auteur ; Clément Mallet , Auteur ; Nesrine Chehata , Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2014 Conférence : IGARSS 2014, International Geoscience And Remote Sensing Symposium 13/07/2014 18/07/2014 Québec Québec - Canada Proceedings IEEE Importance : pp 4315 - 4318 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage automatique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction du réseau routier
[Termes IGN] forêt alpestre
[Termes IGN] France (administrative)
[Termes IGN] montagne
[Termes IGN] processus ponctuel marqué
[Termes IGN] reconnaissance de formes
[Termes IGN] théorie des graphesRésumé : (auteur) In this work, we present an approach that is able to deal with large-scale road network mapping. While former methods focus on delineating patches of roads without computing a coherent road network, we formulate a very large number of road hypothesis that are pruned using a graph reasoning and weak a priori knowledge on road behavior. The initial solution is computed by means of two machine learning and pattern recognition state-of-the-art methods (namely, Random Forest classification and Marked Point Process) that allow to process very large areas in little time with very satisfactory results. Numéro de notice : C2014-024 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IGARSS.2014.6947444 Date de publication en ligne : 06/11/2014 En ligne : http://dx.doi.org/10.1109/IGARSS.2014.6947444 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92029 Documents numériques
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Large scale road network extraction... - pdf auteurAdobe Acrobat PDF A unified framework for land-cover database update and enrichment using satellite imagery / Adrien Gressin (2014)PermalinkUnmixing polarimetric radar images based on land cover type before target decomposition / Sébastien Giordano (2014)PermalinkPermalinkUse intermediate results of wrapper band selection methods: A first step toward the optimization of spectral configuration for land cover classifications / Arnaud Le Bris (2014)PermalinkComparison of VHR panchromatic texture features for tillage mapping / Nesrine Chehata (juillet 2013)PermalinkContribution of texture and red-edge band for vegetated areas detection and identification / Arnaud Le Bris (2013)PermalinkGeneration of an integrated 3D city model with visual landmarks for autonomous navigation in dense urban areas / Bahman Soheilian (June 2013)PermalinkLarge-scale water classification of coastal areas using airborne topographic lidar data / Julien Smeeckaert (juillet 2013)PermalinkMaterial reflectance retrieval in urban tree shadows with physics-based empirical atmospheric correction / Karine R.M. Adeline (2013)PermalinkObject detection and localization using a knowledge graph on spatial relationships / Nguyen-Vu Hoang (July 2013)Permalink