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Per-pixel and object-oriented classification methods for mapping urban land cover extraction using SPOT 5 imagery / Mustafa Neamah Jebur in Geocarto international, vol 29 n° 7 - 8 (November - December 2014)
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Titre : Per-pixel and object-oriented classification methods for mapping urban land cover extraction using SPOT 5 imagery Type de document : Article/Communication Auteurs : Mustafa Neamah Jebur, Auteur ; Helmi Zulhaidi Mohd Shafri, Auteur ; Biswajeet Pradhan, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 792 - 806 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] cartographie urbaine
[Termes IGN] classification dirigée
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] extraction automatique
[Termes IGN] image SPOT 5
[Termes IGN] utilisation du solRésumé : (Auteur) To have sustainable management and proper decision-making, timely acquisition and analysis of surface features are necessary. Traditional pixel-based analysis is the popular way to extract different categories, but it is not comparable by the achievements that can be achieved through the object-based method that uses the additional characteristics of features in the process of classification. In this paper, three types of classification were used to classify SPOT 5 satellite image in mapping land cover; Support vector machine (SVM) pixel-based, SVM object-based and Decision Tree (DT) pixel-based classification. Normalised Difference Vegetation Index and the brightness value of two infrared bands (NIR and SWIR) were used in manually developed DT classification. The classification of the SVM (pixel based) was generated using the selected groups of pixels that represent the selected features. In addition, the SVM (object based) was implemented by using radial-based function kernel. The classified features were oil palm, rubber, urban area, soil, water and other vegetation. The study found that the overall classification of the DT was the lowest at 69.87% while those of SVM (pixel based) and SVM (object based) were 76.67 and 81.25%, respectively. Numéro de notice : A2014-468 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2013.848944 En ligne : https://doi.org/10.1080/10106049.2013.848944 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74045
in Geocarto international > vol 29 n° 7 - 8 (November - December 2014) . - pp 792 - 806[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2014041 RAB Revue Centre de documentation En réserve L003 Disponible A robust image matching method based on optimized BaySAC / Zhizhong Kang in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 11 (November 2014)
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Titre : A robust image matching method based on optimized BaySAC Type de document : Article/Communication Auteurs : Zhizhong Kang, Auteur ; Fengman Jia, Auteur ; Liqiang Zhang, Auteur Année de publication : 2014 Article en page(s) : pp 1041 - 1052 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] appariement automatique
[Termes IGN] appariement d'images
[Termes IGN] classification bayesienne
[Termes IGN] couple stéréoscopique
[Termes IGN] méthode robuste
[Termes IGN] Ransac (algorithme)
[Termes IGN] SIFT (algorithme)Résumé : (Auteur)This paper proposes a robust image-matching method, which integrates SIFT with the optimized Bayes SAmpling Consensus (BaySAC). As the point correspondences are likely contaminated by outliers, we present a novel robust estimation method involving an efficient RaySAC for eliminating falsely accepted correspondences. The key points of the proposed hypothesis testing algorithm are determining and updating the prior probabilities of pseudo-correspondences. First, we propose a strategy for prior probability determination in terms of the statistical characteristics of a deterministic mathematical model for hypothesis testing. Moreover, the inlier probability updating is simplified based on a memorable form of Bayes' Theorem. The proposed approach is validated on a variety of image pairs. The results indicate that when compared with the performance of RANdom SAmpling Consensus (IIANSAC) and the original BaySAC, the proposed optimized BaySAC consumes less computation and obtains higher matching accuracy when the hypothesis set is contaminated with more outliers. Numéro de notice : A2014-616 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.80.11.1041 En ligne : https://doi.org/10.14358/PERS.80.11.1041 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74922
in Photogrammetric Engineering & Remote Sensing, PERS > vol 80 n° 11 (November 2014) . - pp 1041 - 1052[article]Semi-supervised classification for hyperspectral imagery based on spatial-spectral Label Propagation / L. Wang in ISPRS Journal of photogrammetry and remote sensing, vol 97 (November 2014)
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Titre : Semi-supervised classification for hyperspectral imagery based on spatial-spectral Label Propagation Type de document : Article/Communication Auteurs : L. Wang, Auteur ; Siyuan Hao, Auteur ; Q. Wang, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 123 – 137 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification semi-dirigée
[Termes IGN] filtre de Gabor
[Termes IGN] graphe
[Termes IGN] image hyperspectraleRésumé : (Auteur) Graph-based classification algorithms have gained increasing attention in semi-supervised classification. Nevertheless, the graph cannot fully represent the inherent spatial distribution of the data. In this paper, a new classification methodology based on the spatial-spectral Label Propagation is proposed for semi-supervised classification of hyperspectral imagery. The spatial information was used in two aspects: on the one hand, the spatial features extracted by a 2-D Gabor filter were stacked with spectral features; on the other hand, the width of the Gaussian function, which was used to construct graph, was determined with an adaptive method. Subsequently, the unlabeled samples from the spatial neighbors of the labeled samples were selected and the spatial graph was constructed based on spatial smoothness. Finally, labels were propagated from labeled samples to unlabeled samples with spatial-spectral graph to update the training set for a basic classifier (e.g., Support Vector Machine, SVM). Experiments on four hyperspectral datasets show that the proposed Spatial-Spectral Label Propagation based on the SVM (SS-LPSVM) can effectively represent the spatial information in the framework of semi-supervised learning and consistently produces greater classification accuracy than the standard SVM, the Laplacian Support Vector Machine (LapSVM), Transductive Support Vector Machine (TSVM) and the Spatial-Contextual Semi-Supervised Support Vector Machine (SCS3VM). Numéro de notice : A2014-527 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.08.016 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.08.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74140
in ISPRS Journal of photogrammetry and remote sensing > vol 97 (November 2014) . - pp 123 – 137[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2014111 RAB Revue Centre de documentation En réserve L003 Disponible Apport de l'imagerie très haute résolution spatiale pour la caractérisation de la densité urbaine / Laurent Bouffier in Revue Française de Photogrammétrie et de Télédétection, n° 208 (Octobre 2014)
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Titre : Apport de l'imagerie très haute résolution spatiale pour la caractérisation de la densité urbaine Type de document : Article/Communication Auteurs : Laurent Bouffier, Auteur ; Dominique Hébrard, Auteur ; Benoit Mingam, Auteur ; et al., Auteur Année de publication : 2014 Conférence : Pleiades Days 2014 01/04/2014 03/04/2014 Toulouse France Article en page(s) : pp 39 - 44 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] classification dirigée
[Termes IGN] densité du bâti
[Termes IGN] image à très haute résolution
[Termes IGN] image Pléiades
[Termes IGN] Toulouse
[Termes IGN] zone d'aménagement concerté
[Termes IGN] zone homogèneRésumé : (Auteur) Les récentes évolutions règlementaires imposent aux services de l’Etat et aux collectivités de mener une politique d’aménagement urbain combinant construction de logements et gestion économe de l’espace. Le portage de ces politiques sensibles nécessite une connaissance fine, fiable, consensuelle et actualisée du territoire. Les bases de données actuellement disponibles, qui présentent par ailleurs des atouts reconnus, montrent cependant certaines limites bloquantes en termes d’homogénéité ou de fréquence de mise à jour. L’objectif de cette étude est d’identifier dans quelle mesure des traitements automatiques sur images satellites à très haute résolution spatiale permettent d’aller au-delà de ces limites et peuvent fournir des informations d’occupation des sols et de densité urbaine. Des couches d’occupation des sols sur l’agglomération toulousaine sont obtenues par classifications supervisées sur images Pléiades. Les surfaces de bâti sont ensuite agglomérées à l’îlot urbain pour définir des indicateurs liés aux documents de planification. Numéro de notice : A2014-606 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article DOI : 10.52638/rfpt.2014.97 En ligne : https://doi.org/10.52638/rfpt.2014.97 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74906
in Revue Française de Photogrammétrie et de Télédétection > n° 208 (Octobre 2014) . - pp 39 - 44[article]Mathematical morphology pre-processing for enhanced segmentation of heterogeneous spatial regions / Julien Radoux in Revue Française de Photogrammétrie et de Télédétection, n° 208 (Octobre 2014)
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Titre : Mathematical morphology pre-processing for enhanced segmentation of heterogeneous spatial regions Type de document : Article/Communication Auteurs : Julien Radoux, Auteur ; Pierre Defourny, Auteur Année de publication : 2014 Conférence : Pleiades Days 2014 01/04/2014 03/04/2014 Toulouse France Article en page(s) : pp 33 - 38 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] délimitation
[Termes IGN] image Pléiades
[Termes IGN] morphologie mathématique
[Termes IGN] segmentation d'imageRésumé : (Auteur) The very high spatial resolution of Pleiades images allows for the detection of small spatial objects such as buildings or isolated trees. However, the delineation of spatial regions, defined as associations between different spatial objects (such as open canopy forests or urban areas), becomes more challenging with the high level of details. On one hand, automated image segmentation algorithms often yield over-segmented polygons due to due to the high spectral heterogeneity of those regions. On the other hand, manual delineation was shown to end up with a significant bias from the interpreter and even a lack of consistency when the same person works more than one hour on the same task. In this study, we aimed at implementing a new filter to increase the contextual consistency of automated segmentation while preserving the geometric precision of the delineation of spectrally homogeneous spatial regions. A new mathematical morphology approach is proposed, which consists in applying a set of rules to an image based on the presence of absence of vegetation pixels within a structuring element. Two composite filters were then built based on the new filters. The opening filter removes isolated vegetation patches inside heterogeneous spatial regions, while the closing filter fills the gaps between those vegetation patches. The filters have been tested on a Pleiades images located in Belgium around the city of Leuven. A composite image was then created with the NIR and Red filtered bands stacked with the original image bands. The composite and the original bands were then segmented using e-Cognition software with the same parameters. The results show that the segmentation of the filtered images is spatially more consistent than the segmentation based on the unfiltered image. The over-segmentation is reduced in the heterogeneous areas, while the precision of the delineation is improved. The objects derived from the filtered images are thus more appropriate for the monitoring of spatial regions. Numéro de notice : A2014-605 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.52638/rfpt.2014.133 En ligne : https://doi.org/10.52638/rfpt.2014.133 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74905
in Revue Française de Photogrammétrie et de Télédétection > n° 208 (Octobre 2014) . - pp 33 - 38[article]Object-based hyperspectral classification of urban areas using marker-based hierarchical segmentation / Davood Akbari in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 10 (October 2014)
PermalinkQuantification et cartographie de la structure forestière à partir de la texture des images Pléiades / Benoit Beguet in Revue Française de Photogrammétrie et de Télédétection, n° 208 (Octobre 2014)
PermalinkSubspace-based technique for speckle noise reduction in SAR images / Norashikin Yahya in IEEE Transactions on geoscience and remote sensing, vol 52 n° 10 tome 1 (October 2014)
PermalinkToward satellite-based land cover classification through optimum-path forest / Rodrigo José Pisani in IEEE Transactions on geoscience and remote sensing, vol 52 n° 10 tome 1 (October 2014)
PermalinkSemantic 3D scene interpretation: A framework combining optimal neighborhood size selection with relevant features / Martin Weinmann in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 (September 2014)
PermalinkPermalinkCharacterisation of building alignments with new measures using C4.5 decision tree algorithm / Sinan Cetinkaya in Geodetski vestnik, vol 58 n° 3 ([01/09/2014])
PermalinkClassification of submerged aquatic vegetation in Black River using hyperspectral image analysis / Roshan Pande-Chhetri in Geomatica, vol 68 n° 3 (September 2014)
PermalinkDetection of systematic displacements in spatial databases using linear elements / A. Mozas-Calvache in Cartography and Geographic Information Science, vol 41 n° 4 (September 2014)
PermalinkIGS-MGEX, on prépare le terrain pour les sciences et techniques GNSS multi-constellation / Oliver Montenbruck in XYZ, n° 140 (septembre - novembre 2014)
PermalinkLand cover and soil type mapping from spaceborne PolSAR Data at L-Band with probabilistic neural network / Oleg Antropov in IEEE Transactions on geoscience and remote sensing, vol 52 n° 9 Tome 1 (September 2014)
PermalinkSpectral-angle-based Laplacian Eigenmaps for non linear dimensionality reduction of hyperspectral imagery / L. Yan in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 9 (September 2014)
PermalinkA user study of experimental maps for outdoor activities / Juha Oksanen in Cartographica, vol 49 n° 3 (September 2014)
PermalinkAn intelligent approach towards automatic shape modelling and object extraction from satellite images using cellular automata based algorithm / P. V. Arun in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)
PermalinkA class of cloud detection algorithms based on a MAP-MRF approach in space and time / Gemine Vivone in IEEE Transactions on geoscience and remote sensing, vol 52 n° 8 Tome 2 (August 2014)
PermalinkEstimation of the timber quality of scots pine with terrestrial laser scanning / Ville Kankare in Forests, vol 5 n° 8 (August 2014)
PermalinkGeospatial method for computing supplemental multi-decadal US coastal land use and land cover classification products, using Landsat data and C-CAP products / Joseph P. Spruce in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)
PermalinkHyperspectral data dimensionality reduction and the impact of multi-seasonal Hyperion EO-1 imagery on classification accuracies of tropical forest species / Manjit Saini in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 8 (August 2014)
PermalinkHyperspectral remote sensing image subpixel target detection based on supervised metric learning / Lefei Zhang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 8 Tome 2 (August 2014)
PermalinkKernel sparse multitask learning for hyperspectral image classification with empirical mode decomposition and morphological wavelet-based features / Z. He in IEEE Transactions on geoscience and remote sensing, vol 52 n° 8 Tome 2 (August 2014)
PermalinkRoad hierarchy with integration of attributes using fuzzy-AHP / Fatih Gülgen in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)
PermalinkA rule-based parameter aided with object-based classification approach for extraction of building and roads from WorldView-2 images / Zahra Ziaei in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)
PermalinkApproche de détermination de signature de texture : application à la classification de couverts forestiers d’image satellitaire à haute résolution / Wala Zaaboub in Revue Française de Photogrammétrie et de Télédétection, n° 207 (Juillet 2014)
PermalinkLand cover classification of finer resolution remote sensing data integrating temporal features from time series coarser resolution data / Kun Jia in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)
PermalinkNovel Folded-PCA for improved feature extraction and data reduction with hyperspectral imaging and SAR in remote sensing / Jaime Zabalza in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)
PermalinkPermalinkAn effective morphological index in automatic recognition of built-up area suitable for high spatial resolution images as ALOS and SPOT data / Bo Yu in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 6 (June 2014)
PermalinkUne approche basée objet combinée avec les classifieurs avancés (SVM, RF, Extra Trees) pour la détection des changements du bâti / Loubna Elmansouri in Revue internationale de géomatique, vol 24 n° 2 (juin - août 2014)
PermalinkCrop type classification by simultaneous use of satellite images of different resolutions / Mark W. Liu in IEEE Transactions on geoscience and remote sensing, vol 52 n° 6 Tome 2 (June 2014)
PermalinkDecision fusion in kernel-induced spaces for hyperspectral image classification / Wei Li in IEEE Transactions on geoscience and remote sensing, vol 52 n° 6 Tome 2 (June 2014)
PermalinkDevelopment of fuzzy rule-based parameters for urban object-oriented classification using very high resolution imagery / Alireza Hamedianfar in Geocarto international, vol 29 n° 3 - 4 (June - July 2014)
PermalinkDiscrimination des unités géologiques et structurales du socle précambrien de l'Afrique de l'ouest à l'aide de transformations multispectrales : cas du degré carré de Korhogo au nord de la Côte d'Ivoire / K. Kouamé in Photo interprétation, European journal of applied remote sensing, vol 50 n° 2 (juin 2014)
PermalinkLes effets de l'oscillation Nord-Atlantique sur les transferts de masse, vus par géodésie / Pierre Valty in XYZ, n° 139 (juin - août 2014)
PermalinkFeature extraction of hyperspectral images with image fusion and recursive filtering / Xudong Kang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 6 Tome 2 (June 2014)
PermalinkMapping large spatial flow data with hierarchical clustering / Xi Zhu in Transactions in GIS, vol 18 n° 3 (June 2014)
PermalinkPerformance evaluation of object-based and pixel-based building detection algorithms from very high spatial resolution imagery / Iman Khosravi in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 6 (June 2014)
PermalinkSemisupervised dual-geometric subspace projection for dimensionality reduction of hyperspectral image data / Shuyuan Yang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 6 Tome 2 (June 2014)
PermalinkSignificance analysis of different types of ancillary geodata utilized in a multisource classification process for forest identification in Germany / Michael Förster in IEEE Transactions on geoscience and remote sensing, vol 52 n° 6 Tome 2 (June 2014)
PermalinkActive learning in the spatial domain for remote sensing image classification / André Stumpf in IEEE Transactions on geoscience and remote sensing, vol 52 n° 5 tome 1 (May 2014)
PermalinkAmadeus : analyse de données massives en sciences de la Terre et de l'univers / Collectif Amadeus in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 19 n° 3 (mai - juin 2014)
PermalinkBig data : mise en perspective et enjeux pour les entreprises / Myriam Karoui in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 19 n° 3 (mai - juin 2014)
PermalinkBayesian context-dependent learning for anomaly classification in hyperspectral imagery / Christopher Ratto in IEEE Transactions on geoscience and remote sensing, vol 52 n° 4 (April 2014)
PermalinkA general framework for trajectory data warehousing and visual OLAP / Luca Leonardi in Geoinformatica, vol 18 n° 2 (April 2014)
PermalinkAutomatic registration of coastal remotely sensed imagery by affine invariant feature matching with shoreline constraint / Liang Cheng in Marine geodesy, vol 37 n° 1 (March - May 2014)
PermalinkEfficient, simultaneous detection of multi-class geospatial targets based on visual saliency modeling and discriminative learning of sparse coding / Junwei Han in ISPRS Journal of photogrammetry and remote sensing, vol 89 (March 2014)
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