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Spatial and spectral image fusion using sparse matrix factorization / Bo Huang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 3 (March 2014)
[article]
Titre : Spatial and spectral image fusion using sparse matrix factorization Type de document : Article/Communication Auteurs : Bo Huang, Auteur ; Huihui Song, Auteur ; Hengbin Cui, Auteur ; Jigen Peng, Auteur ; Zongben Xu, Auteur Année de publication : 2014 Article en page(s) : pp 1693 - 1704 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse combinatoire (maths)
[Termes IGN] apprentissage automatique
[Termes IGN] factorisation
[Termes IGN] fusion d'images
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Terra-MODIS
[Termes IGN] matrice creuse
[Termes IGN] pouvoir de résolution géométrique
[Termes IGN] pouvoir de résolution spectraleRésumé : (Auteur) In this paper, we present a novel spatial and spectral fusion model (SASFM) that uses sparse matrix factorization to fuse remote sensing imagery with different spatial and spectral properties. By combining the spectral information from sensors with low spatial resolution (LSaR) but high spectral resolution (HSeR) (hereafter called HSeR sensors), with the spatial information from sensors with high spatial resolution (HSaR) but low spectral resolution (LSeR) (hereafter called HSaR sensors), the SASFM can generate synthetic remote sensing data with both HSaR and HSeR. Given two reasonable assumptions, the proposed model can integrate the LSaR and HSaR data via two stages. In the first stage, the model learns from the LSaR data a spectral dictionary containing pure signatures, and in the second stage, the desired HSaR and HSeR data are predicted using the learned spectral dictionary and the known HSaR data. The SASFM is tested with both simulated data and actual Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) acquisitions, and it is also compared to other representative algorithms. The experimental results demonstrate that the SASFM outperforms other algorithms in generating fused imagery with both the well-preserved spectral properties of MODIS and the spatial properties of ETM+. Generated imagery with simultaneous HSaR and HSeR opens new avenues for applications of MODIS and ETM+. Numéro de notice : A2014-115 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2253612 En ligne : https://doi.org/10.1109/TGRS.2013.2253612 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33020
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 3 (March 2014) . - pp 1693 - 1704[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2014031 RAB Revue Centre de documentation En réserve L003 Disponible vol 19 n° 2 - mars - avril 2014 - Vers une adaptation dynamique et contextuelle des systèmes d'information (Bulletin de Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI) / Chantal Soulé-Dupuy
[n° ou bulletin]
est un bulletin de Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI (2001 -)
Titre : vol 19 n° 2 - mars - avril 2014 - Vers une adaptation dynamique et contextuelle des systèmes d'information Type de document : Périodique Auteurs : Chantal Soulé-Dupuy, Éditeur scientifique Année de publication : 2014 Importance : 136 p. Langues : Français (fre) Descripteur : [Vedettes matières IGN] Systèmes d'information
[Termes IGN] analyse de données
[Termes IGN] données massives
[Termes IGN] exploration de données
[Termes IGN] flux de données
[Termes IGN] socle
[Termes IGN] système d'informationNuméro de notice : 093-201402 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE/SOCIETE NUMERIQUE Nature : Numéro de périodique En ligne : http://isi.revuesonline.com/resnum.jsp Format de la ressource électronique : URL sommaire Permalink : https://documentation.ensg.eu/index.php?lvl=bulletin_display&id=17469 [n° ou bulletin]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 093-2014021 SL Revue Centre de documentation Revues en salle Disponible 093-2014031 SL Revue Centre de documentation Revues en salle Disponible Adaptive subpixel mapping based on a multiagent system for remote-sensing imagery / Xiong Xu in IEEE Transactions on geoscience and remote sensing, vol 52 n° 2 (February 2014)
[article]
Titre : Adaptive subpixel mapping based on a multiagent system for remote-sensing imagery Type de document : Article/Communication Auteurs : Xiong Xu, Auteur ; Yanfei Zhong, Auteur ; Liangpei Zhang, Auteur Année de publication : 2014 Article en page(s) : pp 787 - 804 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] analyse infrapixellaire
[Termes IGN] image à ultra haute résolution
[Termes IGN] système multi-agentsRésumé : (Auteur) The existence of mixed pixels is a major problem in remote-sensing image classification. Although the soft classification and spectral unmixing techniques can obtain an abundance of different classes in a pixel to solve the mixed pixel problem, the subpixel spatial attribution of the pixel will still be unknown. The subpixel mapping technique can effectively solve this problem by providing a fine-resolution map of class labels from coarser spectrally unmixed fraction images. However, most traditional subpixel mapping algorithms treat all mixed pixels as an identical type, either boundary-mixed pixel or linear subpixel, leading to incomplete and inaccurate results. To improve the subpixel mapping accuracy, this paper proposes an adaptive subpixel mapping framework based on a multiagent system for remote-sensing imagery. In the proposed multiagent subpixel mapping framework, three kinds of agents, namely, feature detection agents, subpixel mapping agents and decision agents, are designed to solve the subpixel mapping problem. Experiments with artificial images and synthetic remote-sensing images were performed to evaluate the performance of the proposed subpixel mapping algorithm in comparison with the hard classification method and other subpixel mapping algorithms: subpixel mapping based on a back-propagation neural network and the spatial attraction model. The experimental results indicate that the proposed algorithm outperforms the other two subpixel mapping algorithms in reconstructing the different structures in mixed pixels. Numéro de notice : A2014-072 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2244095 En ligne : https://doi.org/10.1109/TGRS.2013.2244095 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32977
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 2 (February 2014) . - pp 787 - 804[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2014021 RAB Revue Centre de documentation En réserve L003 Disponible Bi-temporal texton forest for land cover transition detection on remotely sensed imagery / Zhen Lei in IEEE Transactions on geoscience and remote sensing, vol 52 n° 2 (February 2014)
[article]
Titre : Bi-temporal texton forest for land cover transition detection on remotely sensed imagery Type de document : Article/Communication Auteurs : Zhen Lei, Auteur ; Tao Fang, Auteur ; Hong Huo, Auteur ; Deren Li, Auteur Année de publication : 2014 Article en page(s) : pp 1227 - 1237 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] arbre de décision
[Termes IGN] détection de changement
[Termes IGN] gradient
[Termes IGN] occupation du solRésumé : (Auteur) With the advancement of machine learning, classification methods have been increasingly used in change (or transition) detection. The texton forest (TF)-based method has received increasing research attention because of its speed, good generalization characteristics, stability, and especially its ability to capture spatial contextual information. In this paper, we propose a TF-based method for transition detection in remotely sensed imagery. We investigate a maximal joint-information gain criterion for random forests to better capture combined information in the bi-temporal images in transition detection, which is implemented by a natural extension of binary-trees in traditional methods into a quad-decision tree structure. We also utilize color-invariant gradient as a feature to help alleviate the impact of difference in imaging conditions on bi-temporal transition detection. The experimental results for transition detection show that our bi-temporal TF classifier achieves better performance than a post-classification comparison method and several other alternative methods. Numéro de notice : A2014-075 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2248738 En ligne : https://doi.org/10.1109/TGRS.2013.2248738 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32980
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 2 (February 2014) . - pp 1227 - 1237[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2014021 RAB Revue Centre de documentation En réserve L003 Disponible Combining Geo-SOM and hierarchical clustering to explore geospatial data / Chen-Chieh Feng in Transactions in GIS, vol 18 n° 1 (February 2014)
[article]
Titre : Combining Geo-SOM and hierarchical clustering to explore geospatial data Type de document : Article/Communication Auteurs : Chen-Chieh Feng, Auteur ; Yi-Chen Wang, Auteur ; Chih-Yuan Chen, Auteur Année de publication : 2014 Article en page(s) : pp 125 - 146 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse combinatoire (maths)
[Termes IGN] analyse de groupement
[Termes IGN] carte de Kohonen
[Termes IGN] données localisées
[Termes IGN] exploration de données géographiques
[Termes IGN] visualisationRésumé : (Auteur) Geo-SOM is a useful geovisualization technique for revealing patterns in spatial data, but is ineffective in supporting interactive exploration of patterns hidden in different Geo-SOM sizes. Based on the divide and group principle in geovisualization, the article proposes a new methodology that combines Geo-SOM and hierarchical clustering to tackle this problem. Geo-SOM was used to “divide” the dataset into several homogeneous subsets; hierarchical clustering was then used to “group” neighboring homogeneous subsets for pattern exploration in different levels of granularity, thus permitting exploration of patterns at multiple scales. An artificial dataset was used for validating the method's effectiveness. As a case study, the rush hour motorcycle flow data in Taipei City, Taiwan were analyzed. Compared with the best result generated solely by Geo-SOM, the proposed method performed better in capturing the homogeneous zones in the artificial dataset. For the case study, the proposed method discovered six clusters with unique data and spatial patterns at different levels of granularity, while the original Geo-SOM only identified two. Among the four hierarchical clustering methods, Ward's clustering performed the best in pattern discovery. The results demonstrated the effectiveness of the approach in visually and interactively exploring data and spatial patterns in geospatial data. Numéro de notice : A2014-068 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12025 Date de publication en ligne : 16/09/2013 En ligne : https://doi.org/10.1111/tgis.12025 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32973
in Transactions in GIS > vol 18 n° 1 (February 2014) . - pp 125 - 146[article]Combining RapidEye and lidar satellite imagery for mapping of mining and mine reclamation / Aaron E. Maxwell in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 2 (February 2014)PermalinkDetecting subcanopy invasive plant species in tropical rainforest by integrating optical and microwave (InSAR/PolInSAR) remote sensing data, and a decision tree algorithm / Abduwasit Ghulam in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)PermalinkMulti-agent recognition system based on object based image analysis using WorldView-2 / Fatemeh Tabib Mahmoudi in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 2 (February 2014)PermalinkMultiagent object-based classifier for high spatial resolution imagery / Yanfei Zhong in IEEE Transactions on geoscience and remote sensing, vol 52 n° 2 (February 2014)PermalinkMultiple-entity based classification of airborne laser scanning data in urban areas / S. Xu in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)PermalinkUse of artificial neural networks for selective omission in updating road networks / Qi Zhou in Cartographic journal (the), vol 51 n° 1 (February 2014)PermalinkExtension de l’étiquetage géographique des pixels d’une image par fouille de données / Adrien Gressin in Revue des Nouvelles Technologies de l'Information, E.26 ([23/01/2014])PermalinkActive learning of user’s preferences estimation towards a personalized 3D navigation of geo-referenced scenes / Christos Yiakoumettis in Geoinformatica, vol 18 n° 1 (January 2014)PermalinkAgricultural field delimitation using active learning and random forests margin / Karim Ghariani (2014)PermalinkAssessing the performance of two unsupervised dimensionality reduction techniques on hyperspectral APEX data for high resolution urban land-cover mapping / Luca Demarchi in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)Permalink