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Information content of very high resolution SAR images: study of feature extraction and imaging parameters / Corneliu Dimitru in IEEE Transactions on geoscience and remote sensing, vol 51 n° 8 (August 2013)
[article]
Titre : Information content of very high resolution SAR images: study of feature extraction and imaging parameters Type de document : Article/Communication Auteurs : Corneliu Dimitru, Auteur ; Mihai Datcu, Auteur Année de publication : 2013 Article en page(s) : pp 4591 - 4610 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] angle d'incidence
[Termes IGN] Berlin
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] filtre de Gabor
[Termes IGN] image radar moirée
[Termes IGN] image TerraSAR-X
[Termes IGN] matrice de co-occurrence
[Termes IGN] orbite
[Termes IGN] Ottawa
[Termes IGN] Toulouse
[Termes IGN] transformation de Fourier
[Termes IGN] VeniseRésumé : (Auteur) In this paper, we propose to study the dependence of information extraction technique performance on synthetic aperture radar (SAR) imaging parameters and the selected primitive features (PFs). The evaluation is done on TerraSAR-X data, and the interpretation is realized automatically. In the first part of this paper (use case I), the following issues are analyzed: 1) finding the optimal TerraSAR-X products and their limits of variability and 2) retrieving the number of categories/classes that can be extracted from the TerraSAR-X images using the PFs (gray-level co-occurrence matrix, Gabor filters, quadrature mirror filters, and nonlinear short-time Fourier transform). In the second part of this paper (use case II), we investigate the invariance of the products with the orbit direction and incidence angle. On the one hand, the results show that using ascending looking is better than using descending looking with an average accuracy increase of 7%-8%, approximately. On the other hand, the classification accuracy for the incidence angle varies from a lower value of the incidence to an upper value of the incidence angle (depending on the sensor range) with 4%-5%. The test sites are Venice (Italy), Toulouse (France), Berlin (Germany), and Ottawa (Canada) and are covering as much as possible the huge diversity of modes, types, and geometric resolution configuration of the TerraSAR-X. For the evaluation of all these parameters (resolution, features, orbit looking, and incidence angle), the support-vector-machine classifier is considered. To evaluate the accuracy of the classification, the precision/recall metric is calculated. The first contribution of this paper is the evaluation of different PFs (proposed in the literature for different types of images) and adaptation of these for SAR images. These features are compared (based on the accuracy of the classification) for the first time for a multiresolution pyramid specially built for this purpose. During the evaluation,- all the classes were annotated, and a semantic meaning was defined for each class. The second main contribution of this paper is the evaluation of the dependence on the patch size, orbit direction, and incidence angle of the TerraSAR-X. This type of evaluation has not been systematically investigated so far. For the evaluation of the optimal patch, two different patch sizes were defined, with the constrained that the size on ground needs to cover a minimum of one object (e.g., 200 * 200 m on ground). This patch size depends also on the parameters of the data such as resolution and pixel spacing. The investigation of orbit looking and incidence angle is very important for indexing large data sets that has a higher variability of these two parameters. These parameters influence the accuracy of the classification (e.g., if the incidence angle is closer to the lower bounds or closer to the upper bound of the satellite sensor range). Numéro de notice : A2013-423 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2265413 En ligne : https://doi.org/10.1109/TGRS.2013.2265413 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32561
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 8 (August 2013) . - pp 4591 - 4610[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013081 RAB Revue Centre de documentation En réserve L003 Disponible Estimating tropical forest biomass with a combination of SAR image texture and Landsat TM data: An assessment of predictions between regions / M. Cutler in ISPRS Journal of photogrammetry and remote sensing, vol 70 (June 2012)
[article]
Titre : Estimating tropical forest biomass with a combination of SAR image texture and Landsat TM data: An assessment of predictions between regions Type de document : Article/Communication Auteurs : M. Cutler, Auteur ; D. Boyd, Auteur ; Giles M. Foody, Auteur ; A. Vetrivel, Auteur Année de publication : 2012 Article en page(s) : pp 66 - 77 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] analyse comparative
[Termes IGN] analyse texturale
[Termes IGN] biomasse
[Termes IGN] biomasse (combustible)
[Termes IGN] Brésil
[Termes IGN] classification par réseau neuronal
[Termes IGN] déboisement
[Termes IGN] forêt tropicale
[Termes IGN] image JERS
[Termes IGN] image Landsat-TM
[Termes IGN] image multibande
[Termes IGN] image radar
[Termes IGN] Malaisie
[Termes IGN] matrice de co-occurrence
[Termes IGN] niveau de gris (image)
[Termes IGN] ondelette
[Termes IGN] texture d'image
[Termes IGN] ThaïlandeRésumé : (Auteur) Quantifying the above ground biomass of tropical forests is critical for understanding the dynamics of carbon fluxes between terrestrial ecosystems and the atmosphere, as well as monitoring ecosystem responses to environmental change. Remote sensing remains an attractive tool for estimating tropical forest biomass but relationships and methods used at one site have not always proved applicable to other locations. This lack of a widely applicable general relationship limits the operational use of remote sensing as a method for biomass estimation, particularly in high biomass ecosystems. Here, multispectral Landsat TM and JERS-1 SAR data were used together to estimate tropical forest biomass at three separate geographical locations: Brazil, Malaysia and Thailand. Texture measures were derived from the JERS-1 SAR data using both wavelet analysis and Grey Level Co-occurrence Matrix methods, and coupled with multispectral data to provide inputs to artificial neural networks that were trained under four different training scenarios and validated using biomass measured from 144 field plots. When trained and tested with data collected from the same location, the addition of SAR texture to multispectral data showed strong correlations with above ground biomass (r = 0.79, 0.79 and 0.84 for Thailand, Malaysia and Brazil respectively). Also, when networks were trained and tested with data from all three sites, the strength of correlation (r = 0.55) was stronger than previously reported results from the same sites that used multispectral data only. Uncertainty in estimating AGB from different allometric equations was also tested but found to have little effect on the strength of the relationships observed. The results suggest that the inclusion of SAR texture with multispectral data can go someway towards providing relationships that are transferable across time and space, but that further work is required if satellite remote sensing is to provide robust and reliable methodologies for initiatives such as Reducing Emissions from Deforestation and Degradation (REDD+). Numéro de notice : A2012-289 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.03.011 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.03.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31735
in ISPRS Journal of photogrammetry and remote sensing > vol 70 (June 2012) . - pp 66 - 77[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2012041 SL Revue Centre de documentation Revues en salle Disponible Classification of very high spatial resolution imagery based on the fusion of edge and multispectral information / X. Huang in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 12 (December 2008)
[article]
Titre : Classification of very high spatial resolution imagery based on the fusion of edge and multispectral information Type de document : Article/Communication Auteurs : X. Huang, Auteur ; L. Zhang, Auteur ; P. Li, Auteur Année de publication : 2008 Article en page(s) : pp 1585 - 1596 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse en composantes indépendantes
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection de contours
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image à résolution subdecamétrique
[Termes IGN] image à très haute résolution
[Termes IGN] image multibande
[Termes IGN] image Quickbird
[Termes IGN] matrice de co-occurrence
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] prise en compte du contexteRésumé : (Auteur) A new algorithm based on the fusion of edge and multispectral information is proposed for the pixel-wise classification of very high-resolution (VHR) remotely sensed imagery. It integrates the multispectral, spatial and structural information existing in the image. The edge feature is first extracted using an improved multispectral edge detection method, which takes into account the original multispectral bands, the linear NDVI, and the independent spectral components extracted by independent component analysis (ICA). Direction-lines are then defined using the edge and multispectral information. Two effective spatial measures are calculated based on the direction-lines in order to describe the contextual information and strengthen the multispectral feature space. Then, the support vector machine (SVM) is employed to classify the hybrid structural-multispectral feature set. In experiments, the proposed spatial measures were compared with the pixel shape index (PSI) and the gray level co-occurrence matrix (GLCM). The experimental results show that the proposed algorithm performs well in terms of classification accuracies and visual interpretation. Copyright ASPRS Numéro de notice : A2008-479 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.74.12.1585 En ligne : https://doi.org/10.14358/PERS.74.12.1585 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29548
in Photogrammetric Engineering & Remote Sensing, PERS > vol 74 n° 12 (December 2008) . - pp 1585 - 1596[article]Using co-occurrence models for placename disambiguation / S. Overell in International journal of geographical information science IJGIS, vol 22 n° 3 (march 2008)
[article]
Titre : Using co-occurrence models for placename disambiguation Type de document : Article/Communication Auteurs : S. Overell, Auteur ; S. Ruger, Auteur Année de publication : 2008 Article en page(s) : pp 265 - 287 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données
[Termes IGN] accès aux données localisées
[Termes IGN] matrice de co-occurrence
[Termes IGN] recherche d'information géographique
[Termes IGN] résolution d'ambiguïté
[Termes IGN] toponymeRésumé : (Auteur) This paper describes the generation of a model capturing information on how placenames co-occur together. The advantages of the co-occurrence model over traditional gazetteers are discussed and the problem of placename disambiguation is presented as a case study. We begin by outlining the problem of ambiguous placenames. We demonstrate how analysis of Wikipedia can be used in the generation of a co-occurrence model. The accuracy of our model is compared to a handcrafted ground truth; then we evaluate alternative methods of applying this model to the disambiguation of placenames in free text (using the GeoCLEF evaluation forum). We conclude by showing how the inclusion of placenames in both the text and geographic parts of a query provides the maximum mean average precision and outline the benefits of a co-occurrence model as a data source for the wider field of geographic information retrieval (GIR). Copyright Taylor & Francis Numéro de notice : A2008-139 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810701626236 En ligne : https://doi.org/10.1080/13658810701626236 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29134
in International journal of geographical information science IJGIS > vol 22 n° 3 (march 2008) . - pp 265 - 287[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-08021 RAB Revue Centre de documentation En réserve L003 Disponible 079-08022 RAB Revue Centre de documentation En réserve L003 Disponible Detection, segmentation and characterisation of vegetation in high-resolution aerial images for 3D city modelling / Corina Iovan (2008)
Titre : Detection, segmentation and characterisation of vegetation in high-resolution aerial images for 3D city modelling Type de document : Article/Communication Auteurs : Corina Iovan , Auteur ; Didier Boldo , Auteur ; Matthieu Cord, Auteur Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2008 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 37-B3 Conférence : ISPRS 2008, 21st ISPRS world congress 03/07/2008 11/07/2008 Pékin Chine OA ISPRS Archives Importance : pp 247 - 252 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse texturale
[Termes IGN] arbre (flore)
[Termes IGN] caractérisation
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection automatique
[Termes IGN] espèce végétale
[Termes IGN] houppier
[Termes IGN] image aérienne
[Termes IGN] image infrarouge couleur
[Termes IGN] matrice de co-occurrence
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] modèle numérique de surface
[Termes IGN] reconnaissance de formes
[Termes IGN] segmentation d'imageRésumé : (Auteur) An approach for tree species classification in urban areas from high resolution colour infrared (CIR) aerial images and the corresponding Digital Surface Model (DSM) is described in this paper. The proposed method is a supervised classification one based on a Support Vector Machines (SVM) classifier. Texture features from the Gray Level Co-occurrence Matrix (GLCM) are computed to form feature vectors for both per-pixel and per-region classification approaches. The two approaches are presented and results obtained are evaluated and compared both against each other and also against a manual defined ground truth. To perform tree species classification on highdensity urban area images, trees must previously be segmented into individual objects. All intermediary methods developed to segment individual trees will also be shortly described. Tree parameters (height, crown diameter) are estimated from the DSM. These parameters together with the tree species information are used for a 3D realistic modelling of the trees in urban environments. Results of the described system are presented for a typical scene. Numéro de notice : C2008-023 Affiliation des auteurs : MATIS (1993-2011) Thématique : FORET/IMAGERIE Nature : Communication DOI : sans En ligne : https://www.isprs.org/proceedings/XXXVII/congress/3_pdf/38.pdf Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=64218 Documents numériques
en open access
10667_isprs_2008_iovan.pdfAdobe Acrobat PDF Measuring land development in urban regions using graph theoretical and conditional statistical features / C. Unsalan in IEEE Transactions on geoscience and remote sensing, vol 45 n° 12 Tome 1 (December 2007)PermalinkA pixel shape index coupled with spectral information for classification of high spatial resolution remotely sensed imagery / L. Zhang in IEEE Transactions on geoscience and remote sensing, vol 44 n° 10 Tome 2 (October 2006)PermalinkUtilisation des signatures de texture d'ordre elevé pour une meilleure discrimination des classes d'occupation du sol sur une image radar à synthese d'ouverture / E. Tonye in Revue Française de Photogrammétrie et de Télédétection, n° 179 (Décembre 2005)PermalinkDu choix des mesures dans des procédures de reconnaissance des formes et d'analyse de texture / Mostafa Benali (1987)PermalinkOperateurs d'analyse de texture conduisant à une signature invariante / I. Herlin (1987)PermalinkUtilisation de transformations locales pour l'étude de la texture des images de télédétection / J. Quach (1979)Permalink