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Fast hierarchical segmentation of high-resolution remote sensing images with adaptative edge penalty / Xuellang Zhang in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 1 (January 2014)
[article]
Titre : Fast hierarchical segmentation of high-resolution remote sensing images with adaptative edge penalty Type de document : Article/Communication Auteurs : Xuellang Zhang, Auteur ; Pending Xiao, Auteur ; Xuezhi Feng, Auteur Année de publication : 2014 Article en page(s) : pp 71 - 80 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] image à haute résolution
[Termes IGN] image aérienne
[Termes IGN] image Quickbird
[Termes IGN] image Worldview
[Termes IGN] segmentation d'image
[Termes IGN] segmentation hiérarchique
[Termes IGN] segmentation multi-échelleRésumé : (Auteur) A fast hierarchical segmentation method (FHS) for high-resolution remote sensing (HR) image is proposed in the paper. FHS is completely unsupervised. It is characterized by two aspects. First, the hierarchical segmentation process is accelerated by the improved linear nearest neighbor graph (LNNG) model and the segment tree model. It runs faster than other existing hierarchical segmentation methods, and can produce multi-resolution segmentations in time linear to the image size. Second, an adaptive edge penalty function is introduced to formulate the merging criterion, serving as a semantic factor. A set of QuickBird, WorldView, and aerial images is used to test the proposed method. The experiments show that the multi-resolution segmentations produced by FHS can represent objects at different scales very well. Moreover, the adaptive edge penalty function helps to remove meaningless weak edges within objects, enclosing the relation between segments and real-world objects. Numéro de notice : A2014-093 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.80.1.71 En ligne : https://doi.org/10.14358/PERS.80.1.71 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32998
in Photogrammetric Engineering & Remote Sensing, PERS > vol 80 n° 1 (January 2014) . - pp 71 - 80[article]Geographic Object-Based Image Analysis: Towards a new paradigm / Thomas Blaschke in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)
[article]
Titre : Geographic Object-Based Image Analysis: Towards a new paradigm Type de document : Article/Communication Auteurs : Thomas Blaschke, Auteur ; Geoffrey Hay, Auteur ; Maggi Kelly, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 180 - 191 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse d'image numérique
[Termes IGN] classification
[Termes IGN] information sémantique
[Termes IGN] modèle orienté objet
[Termes IGN] objet géographique
[Termes IGN] ontologie
[Termes IGN] pixel
[Termes IGN] segmentation d'imageRésumé : (Auteur) The amount of scientific literature on (Geographic) Object-based Image Analysis – GEOBIA has been and still is sharply increasing. These approaches to analysing imagery have antecedents in earlier research on image segmentation and use GIS-like spatial analysis within classification and feature extraction approaches. This article investigates these development and its implications and asks whether or not this is a new paradigm in remote sensing and Geographic Information Science (GIScience). We first discuss several limitations of prevailing per-pixel methods when applied to high resolution images. Then we explore the paradigm concept developed by Kuhn (1962) and discuss whether GEOBIA can be regarded as a paradigm according to this definition. We crystallize core concepts of GEOBIA, including the role of objects, of ontologies and the multiplicity of scales and we discuss how these conceptual developments support important methods in remote sensing such as change detection and accuracy assessment. The ramifications of the different theoretical foundations between the ‘per-pixel paradigm’ and GEOBIA are analysed, as are some of the challenges along this path from pixels, to objects, to geo-intelligence. Based on several paradigm indications as defined by Kuhn and based on an analysis of peer-reviewed scientific literature we conclude that GEOBIA is a new and evolving paradigm. Numéro de notice : A2014-019 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.09.014 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.09.014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32924
in ISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 180 - 191[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2014011 RAB Revue Centre de documentation En réserve L003 Disponible Hierarchical extraction of landslides from multiresolution remotely sensed optical images / Camille Kurtz in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)
[article]
Titre : Hierarchical extraction of landslides from multiresolution remotely sensed optical images Type de document : Article/Communication Auteurs : Camille Kurtz, Auteur ; André Stumpf, Auteur ; Jean-Philippe Malet, Auteur ; Pierre Gançarski, Auteur ; Anne Puissant, Auteur ; Nicolas Passat, Auteur Année de publication : 2014 Article en page(s) : pp 122 - 136 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Barcelonnette
[Termes IGN] corrélation par régions de niveaux de gris
[Termes IGN] effondrement de terrain
[Termes IGN] image à résolution submétrique
[Termes IGN] image à ultra haute résolution
[Termes IGN] image Landsat-TM
[Termes IGN] image optique
[Termes IGN] image RapidEye
[Termes IGN] modèle numérique de terrain
[Termes IGN] niveau de détail
[Termes IGN] segmentation d'imageRésumé : (Auteur) The automated detection and mapping of landslides from Very High Resolution (VHR) images present several challenges related to the heterogeneity of landslide sizes, shapes and soil surface characteristics. However, a common geomorphological characteristic of landslides is to be organized with a series of embedded and scaled features. These properties motivated the use of a multiresolution image analysis approach for their detection. In this work, we propose a hybrid segmentation/classification region-based method, devoted to this specific issue. The method, which uses images of the same area at various spatial resolutions (Medium to Very High Resolution), relies on a recently introduced top-down hierarchical framework. In the specific context of landslide analysis, two main novelties are introduced to enrich this framework. The first novelty consists of using non-spectral information, obtained from Digital Terrain Model (DTM), as a priori knowledge for the guidance of the segmentation/classification process. The second novelty consists of using a new domain adaptation strategy, that allows to reduce the expert’s interaction when handling large image datasets. Experiments performed on satellite images acquired over terrains affected by landslides demonstrate the efficiency of the proposed method with different hierarchical levels of detail addressing various operational needs. Numéro de notice : A2014-016 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.11.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.11.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32921
in ISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 122 - 136[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2014011 RAB Revue Centre de documentation En réserve L003 Disponible 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 A local contrast method for small infrared target detection / C.L. Philip Chen in IEEE Transactions on geoscience and remote sensing, vol 52 n° 1 tome 2 (January 2014)
[article]
Titre : A local contrast method for small infrared target detection Type de document : Article/Communication Auteurs : C.L. Philip Chen, Auteur ; Hong Li, Auteur ; Yantao Wei, Auteur ; Tian Xia, Auteur ; Yuan Yan Tang, Auteur Année de publication : 2014 Article en page(s) : pp 574 - 581 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] amélioration du contraste
[Termes IGN] contraste local
[Termes IGN] détection de cible
[Termes IGN] filtrage du bruit
[Termes IGN] image infrarouge
[Termes IGN] rapport signal sur bruit
[Termes IGN] seuillage d'imageRésumé : (Auteur) Robust small target detection of low signal-to-noise ratio (SNR) is very important in infrared search and track applications for self-defense or attacks. Consequently, an effective small target detection algorithm inspired by the contrast mechanism of human vision system and derived kernel model is presented in this paper. At the first stage, the local contrast map of the input image is obtained using the proposed local contrast measure which measures the dissimilarity between the current location and its neighborhoods. In this way, target signal enhancement and background clutter suppression are achieved simultaneously. At the second stage, an adaptive threshold is adopted to segment the target. The experiments on two sequences have validated the detection capability of the proposed target detection method. Experimental evaluation results show that our method is simple and effective with respect to detection accuracy. In particular, the proposed method can improve the SNR of the image significantly. Numéro de notice : A2014-041 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2242477 En ligne : https://doi.org/10.1109/TGRS.2013.2242477 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32946
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 1 tome 2 (January 2014) . - pp 574 - 581[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2014011B RAB Revue Centre de documentation En réserve L003 Disponible Remote sensing image segmentation by combining spectral and texture features / H. Li in IEEE Transactions on geoscience and remote sensing, vol 52 n° 1 tome 1 (January 2014)Permalink3D tree reconstruction from simulated small footprint waveform lidar / Jiaying Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 12 (December 2013)PermalinkAutomated detection of buildings from single VHR multispectral images using shadow information and graph cuts / Ali Ozgun Ok in ISPRS Journal of photogrammetry and remote sensing, vol 86 (December 2013)PermalinkHierarchical method of urban building extraction inspired by human perception / Chao Tao in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 12 (December 2013)PermalinkA combined object- and pixel-based image analysis framework for urban land cover classification of VHR imagery / Bahram Salehi in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 11 (November 2013)PermalinkHomological persistence for shape based change detection between Digital Elevation Models / Bruno Vallet in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 W2 (November 2013)PermalinkNarrow-band interference suppresion for SAR based on independent component analysis / Feng Zhou in IEEE Transactions on geoscience and remote sensing, vol 51 n° 10 (October 2013)PermalinkComparaison entre les méthodes J-SEG et MeanShift : application sur des données THRS / Rabia Sarah Cheriguene in Revue Française de Photogrammétrie et de Télédétection, n° 203 (Juillet 2013)PermalinkIndependent two-step thresholding of binary images in inter-annual land cover change/no-change identification / Priyakant Sinha in ISPRS Journal of photogrammetry and remote sensing, vol 81 (July 2013)PermalinkDerivation of tree skeletons and error assessment using LiDAR point cloud data of varying quality / Magnus Bremer in ISPRS Journal of photogrammetry and remote sensing, vol 80 (June 2013)Permalink