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scientifique

Edge-guided multiscale segmentation of satellite multispectral imagery / J. Chen in IEEE Transactions on geoscience and remote sensing, vol 50 n° 11 Tome 1 (November 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 11 Tome 1 (November 2012) . - pp 4513 - 4520 Titre : Edge-guided multiscale segmentation of satellite multispectral imagery Type de document : Article/Communication Auteurs : J. Chen, Auteur ; J. Li, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 4513 - 4520 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse d'image numérique [Termes IGN] contour [Termes IGN] détection de contours [Termes IGN] filtre de Canny [Termes IGN] image multibande [Termes IGN] littoral [Termes IGN] segmentation d'image Résumé : (Auteur) This paper presents a new approach to multiscale segmentation of satellite multispectral imagery using edge information. The Canny edge detector is applied to perform multispectral edge detection. The detected edge features are then utilized in a multiscale segmentation loop, and the merge procedure for adjacent image objects is controlled by a separability criterion that combines edge information with segmentation scale. The significance of the edge is measured by adjacent partitioned regions to perform edge assessment. The present method is based on a half-partition structure, which is composed of three steps: single edge detection, separated pixel grouping, and significant feature calculation. The spectral distance of the half-partitions separated by the edge is calculated, compared, and integrated into the edge information. The results show that the proposed approach works well on satellite multispectral images of a coastal area. Numéro de notice : A2012-590 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2194502 Date de publication en ligne : 23/05/2012 En ligne : https://doi.org/10.1109/TGRS.2012.2194502 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32036 [article]

An automated approach for updating land cover maps based on integrated change detection and classification methods / X. Chen in ISPRS Journal of photogrammetry and remote sensing, vol 71 (July 2012)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 71 (July 2012) . - pp 86 - 95 Titre : An automated approach for updating land cover maps based on integrated change detection and classification methods Type de document : Article/Communication Auteurs : X. Chen, Auteur ; J. Chen, Auteur ; Y. Shi, Auteur ; Yasushi Yamaguchi, Auteur Année de publication : 2012 Article en page(s) : pp 86 - 95 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] carte d'occupation du sol [Termes IGN] champ aléatoire de Markov [Termes IGN] Chensi (Chine) [Termes IGN] détection de changement [Termes IGN] image Landsat-ETM+ [Termes IGN] mise à jour de base de données Résumé : (Auteur) Updating land cover maps from remotely sensed data in a timely manner is important for many areas of scientific research. Unfortunately, traditional classification procedures are very labor intensive and subjective because of the required human interaction. Based on the strategy of updating land cover data only for the changed area, we proposed an integrated, automated approach to update land cover maps without human interaction. The proposed method consists primarily of the following three parts: a change detection technique, a Markov Random Fields (MRFs) model, and an iterated training sample selecting procedure. In the proposed approach, remotely sensed data acquired in different seasons or from different remote sensors can be used. Meanwhile, the approach is completely unsupervised. Therefore, the methodology has a wide scope of application. A case study of Landsat data was conducted to test the performance of this method. The experimental results show that several sub-modules in this method work effectively and that reasonable classification accuracy can be achieved. Numéro de notice : A2012-350 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.05.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.05.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31796 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2012051	SL	Revue	Centre de documentation	Revues en salle	Disponible

A framework for supervised image classification with incomplete training samples / Q. Guo in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 6 (June 2012)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 78 n° 6 (June 2012) . - pp 595 - 604 Titre : A framework for supervised image classification with incomplete training samples Type de document : Article/Communication Auteurs : Q. Guo, Auteur ; W. Li, Auteur ; J. Chen, Auteur Année de publication : 2012 Article en page(s) : pp 595 - 604 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] carte d'occupation du sol [Termes IGN] classification dirigée [Termes IGN] classification par maximum de vraisemblance [Termes IGN] échantillonnage d'image [Termes IGN] extraction de couche Résumé : (Auteur) For traditional supervised classification methods, all land-cover types need to be exhaustively labeled to train the classifier. However, there are situations where the training sample classes are incomplete due to a lack of understanding of ground cover types in the image. In this study we propose a one-by-one (OBO) classification framework to address this incomplete training sample problem. The OBO approach is based on a one-class classifier (positive and unlabeled learning algorithm), and it extracts the land-cover type from the image one at a time. The performance of the proposed method was compared with a traditional supervised classifier using a high spatial resolution image. The average accuracy of the new method is 76.34 percent across different training sample sizes, whereas the accuracy of the classical approach is 66.46 percent, with an increase of 9.88 percent. The results demonstrate that the proposed new framework provides significantly higher classification accuracy than the classical approach at the 95 percent confidence level, and shows promise in dealing with the incomplete training sample problem for supervised image classification. Numéro de notice : A2012-249 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.78.6.595 En ligne : https://doi.org/10.14358/PERS.78.6.595 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31695 [article]

Modeling and simulation of polarimetric hyperspectral imaging process / Junping Zhang in IEEE Transactions on geoscience and remote sensing, vol 50 n° 6 (June 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 6 (June 2012) . - pp 2238 - 2253 Titre : Modeling and simulation of polarimetric hyperspectral imaging process Type de document : Article/Communication Auteurs : Junping Zhang, Auteur ; J. Chen, Auteur ; B. Zou, Auteur ; Y. Zhang, Auteur Année de publication : 2012 Article en page(s) : pp 2238 - 2253 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] données polarimétriques [Termes IGN] image hyperspectrale [Termes IGN] modélisation de prise de vue [Termes IGN] polarisation [Termes IGN] réflectance végétale [Termes IGN] simulation d'image Résumé : (Auteur) Polarimetric hyperspectral images can provide spectral, spatial, and polarimetric information of a scene, which are unique and comprehensive for remote sensing applications such as growth monitoring of crops, analysis of water quality, and geology mapping, etc. The researches on polarimetric hyperspectral imaging mechanism and on image characteristics are of great importance for further information extraction and utilization of the images. The purposes of this paper are to analyze the mechanism of polarimetric hyperspectral imaging and to model such a process. The outcome of the paper will help designers and users of a polarimetric hyperspectral imaging system to further understand the system and take full advantages of it. In this paper, a polarimetric hyperspectral imaging model is proposed, in which the influence of skylight on polarization is considered, and subpixel model, polarized reflectance models, and the classical fast canopy reflectance model are combined to model the vegetation canopy. Then, a simulated scene that includes a woodland area with low shrubbery and a road is obtained by using the imaging model. Experiments analyze and discuss the simulation condition and parameters of the imaging models, the uniqueness, and usefulness of the integration of polarimetric and spectral information. Numéro de notice : A2012-265 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2172618 Date de publication en ligne : 28/11/2011 En ligne : https://doi.org/10.1109/TGRS.2011.2172618 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31711 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-2012061	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Ionospheric artifacts in simultaneous L-band InSAR and GPS observations / J. Chen in IEEE Transactions on geoscience and remote sensing, vol 50 n° 4 (April 2012)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 50 n° 4 (April 2012) . - pp 11227 - 1239 Titre : Ionospheric artifacts in simultaneous L-band InSAR and GPS observations Type de document : Article/Communication Auteurs : J. Chen, Auteur ; H. Zebker, Auteur Année de publication : 2012 Article en page(s) : pp 11227 - 1239 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] artefact [Termes IGN] bande L [Termes IGN] image ALOS-PALSAR [Termes IGN] image radar moirée [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] propagation ionosphérique [Termes IGN] teneur totale en électrons Résumé : (Auteur) Phase artifacts in interferometric synthetic aperture radar (InSAR) images frequently degrade the interpretability of the phase and correlation signatures of terrain. Often, these distortions are attributed to spatially variable ionospheric propagation delays at two different SAR acquisition times. We present here L-band InSAR data from Iceland, California, and Hawaii. The California and Hawaii interferograms show no significant ionospheric artifacts, while the Iceland interferogram shows a maximum misregistration of three pixels in the azimuth direction, which leads to severe phase decorrelation artifacts in the InSAR image. We relate the misregistration of complex pixels seen in the interferograms to the gradient of the ionospheric total electron content (TEC) observed by global positioning system (GPS) data and confirm that indeed the phase artifacts in the Iceland interferogram are due to dispersive ionospheric propagation rather than other decorrelation factors such as neutral atmospheric delays. We develop a method to measure the spatial TEC variation at synthetic aperture length scales using dual-frequency GPS carrier phase data. We solve for the GPS data ambiguities using a low-resolution ionosphere reference derived from either available ionospheric observations or the GPS carrier phase data themselves. GPS observations show directly the level of ionospheric variability, and the spatial TEC gradient as observed by GPS predicts the misregistration of complex pixels in interferograms in all three areas. This confirmation of the cause of the image artifacts suggests that they can be routinely corrected from the InSAR data alone, provided that the sensor measures the change in TEC along the radar swath. Numéro de notice : A2012-136 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2164805 Date de publication en ligne : 06/10/2011 En ligne : https://doi.org/10.1109/TGRS.2011.2164805 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31584 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-2012041	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Consistency of accuracy assessment indices for soft classification: simulation analysis / J. Chen in ISPRS Journal of photogrammetry and remote sensing, vol 65 n° 2 (March - April 2010)  

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Update-efficient indexing of moving objects in road networks / J. Chen in Geoinformatica, vol 13 n° 4 (December 2009)  

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Geocenter variations derived from GPS tracking of the GRACE satellites / Z. Kang in Journal of geodesy, vol 83 n° 10 (October 2009)  

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Selective omission of road features based on mesh density for automatic map generalization / J. Chen in International journal of geographical information science IJGIS, vol 23 n° 7-8 (july 2009)  

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Resolution control for balancing overview and detail in multivariate spatial analysis / J. Chen in Cartographic journal (the), vol 45 n° 4 (November 2008)  

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ISRV: an improved synthetic variable ratio method for image fusion / L. Wang in Geocarto international, vol 23 n° 2 (April - May 2008)  

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Reconciliation of inconsistent perspectives in collaborative GIS / J. Chen in Cartography and Geographic Information Science, vol 35 n° 2 (April 2008)  

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Advances in photogrammetry, remote sensing and spatial information sciences / Z. Li (2008)

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Supporting the process of exploring and interpreting space-time multivariate patterns: the visual inquiry toolkit / J. Chen in Cartography and Geographic Information Science, vol 35 n° 1 (January 2008)  

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Detection of spatial conflicts between rivers and contours in digital map updating / J. Chen in International journal of geographical information science IJGIS, vol 21 n° 9-10 (october 2007)  

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