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Multiple Spectral–Spatial Classification Approach for Hyperspectral Data / Yuliya Tarabalka in IEEE Transactions on geoscience and remote sensing, vol 48 n° 11 (November 2010)
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Titre : Multiple Spectral–Spatial Classification Approach for Hyperspectral Data Type de document : Article/Communication Auteurs : Yuliya Tarabalka, Auteur ; Jon Atli Benediktsson, Auteur ; Jocelyn Chanussot, Auteur ; James C. Tilton, Auteur Année de publication : 2010 Article en page(s) : pp 4122 - 4132 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification multibande
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] segmentation d'imageRésumé : (Auteur) A new multiple-classifier approach for spectral-spatial classification of hyperspectral images is proposed. Several classifiers are used independently to classify an image. For every pixel, if all the classifiers have assigned this pixel to the same class, the pixel is kept as a marker, i.e., a seed of the spatial region with a corresponding class label. We propose to use spectral-spatial classifiers at the preliminary step of the marker-selection procedure, each of them combining the results of a pixelwise classification and a segmentation map. Different segmentation methods based on dissimilar principles lead to different classification results. Furthermore, a minimum spanning forest is built, where each tree is rooted on a classification-driven marker and forms a region in the spectral-spatial classification map. Experimental results are presented for two hyperspectral airborne images. The proposed method significantly improves classification accuracies when compared with previously proposed classification techniques. Numéro de notice : A2010-480 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2010.2062526 Date de publication en ligne : 13/09/2010 En ligne : https://doi.org/10.1109/TGRS.2010.2062526 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30673
in IEEE Transactions on geoscience and remote sensing > vol 48 n° 11 (November 2010) . - pp 4122 - 4132[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2010111 RAB Revue Centre de documentation En réserve L003 Disponible Noise-signal index threshold: a new noise-reduction technique for generation of reference spectra and efficient hyperspectral image classification / K. Kusuma in Geocarto international, vol 25 n° 7 (November 2010)
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Titre : Noise-signal index threshold: a new noise-reduction technique for generation of reference spectra and efficient hyperspectral image classification Type de document : Article/Communication Auteurs : K. Kusuma, Auteur ; D. Ramakrishnan, Auteur ; H. Pandalai, Auteur ; G. Kailash, Auteur Année de publication : 2010 Article en page(s) : pp 569 - 580 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] bruit blanc
[Termes IGN] classification spectrale
[Termes IGN] correction radiométrique
[Termes IGN] filtrage du bruit
[Termes IGN] modèle empirique
[Termes IGN] réponse spectrale
[Termes IGN] seuillage d'imageRésumé : (Auteur) Reference spectra of terrestrial targets are usually collected using field spectro-radiometers for mineral abundance mapping and target detection. These spectra often have noise that masks characteristic absorption and reflection features and affects the efficiency of material mapping. This work aims at obtaining an empirical technique for reduction of high-frequency noise from field spectra. The proposed noise correction technique uses a 'normalized' measure Rn, where Rn = (Ln - Fn)/Ln for each band (n) calculated from field and laboratory spectra of test material, with Fn and Ln being the depth of the absorption feature in field and laboratory spectra, respectively. On the basis of the assumption of the constancy of this ratio in neighbouring bands, an empirical algorithm that approximates the ratio Rn of a noisy band to the corrected ratio of an adjacent band is used to obtain the noise-corrected field spectra. The classification accuracy increases significantly when noise reduced field spectra are used as reference spectra. Numéro de notice : A2010-471 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2010.510582 Date de publication en ligne : 16/09/2010 En ligne : https://doi.org/10.1080/10106049.2010.510582 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30664
in Geocarto international > vol 25 n° 7 (November 2010) . - pp 569 - 580[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2010071 RAB Revue Centre de documentation En réserve L003 Disponible Understanding chorematic diagrams : towards a taxonomy / Andreas W. Reimer in Cartographic journal (the), vol 47 n° 4 (November 2010)
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Titre : Understanding chorematic diagrams : towards a taxonomy Type de document : Article/Communication Auteurs : Andreas W. Reimer, Auteur Année de publication : 2010 Article en page(s) : pp 330 - 350 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique
[Termes IGN] cartogramme
[Termes IGN] cartologie
[Termes IGN] chorème
[Termes IGN] conception cartographique
[Termes IGN] histoire de la cartographie
[Termes IGN] schéma conceptuel de données
[Termes IGN] taxinomie
[Termes IGN] zone d'intérêtRésumé : (Auteur) Chorematic diagrams are prospective candidates for communicating highly generalised geographic information about a given region of interest. Chorematic diagrams were popularized in France as the graphical artefacts of a specific school of geographic thought established by Roger Brunet, with GIP-RECLUS as his institutional backing. Although many maps were created and a lively debate ensued, only few consolidated cartographic findings were generated and even less were made known to the international scientific community. This article presents a contextualizing review and proposes a cartographic taxonomy aimed at being a first step towards efforts for the automated generation of chorematic diagrams. Numéro de notice : A2010-542 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1179/000870410X12825500202896 Date de publication en ligne : 29/11/2013 En ligne : https://doi.org/10.1179/000870410X12825500202896 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30734
in Cartographic journal (the) > vol 47 n° 4 (November 2010) . - pp 330 - 350[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 030-2010041 RAB Revue Centre de documentation En réserve L003 Disponible Effect of SRTM resolution on morphometric feature identification using neural network - self organizing map / A. Ehsani in Geoinformatica, vol 14 n° 4 (October 2010)
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Titre : Effect of SRTM resolution on morphometric feature identification using neural network - self organizing map Type de document : Article/Communication Auteurs : A. Ehsani, Auteur ; F. Quiel, Auteur ; A. Malekian, Auteur Année de publication : 2010 Article en page(s) : pp 405 - 424 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] aire protégée
[Termes IGN] Carpates
[Termes IGN] carte de Kohonen
[Termes IGN] classification par réseau neuronal
[Termes IGN] détection de changement
[Termes IGN] données topographiques
[Termes IGN] géomorphométrie
[Termes IGN] image SIR-C-X-SAR
[Termes IGN] MNS SRTMRésumé : (Auteur) In this study, we present a semi-automatic procedure using Neural Networks—Self Organizing Map—and Shuttle Radar Topography Mission DEMs to characterize morphometric features of the landscape in the Man and Biosphere Reserve “Eastern Carpathians”. We investigate specially the effect of two resolutions, SIR-C with 3 arc seconds and X-SAR with 1 arc second for morphometric feature identification. Specifically we investigate how the SRTM/C band data with 30 m interpolated grid, corresponding to SRTM/X band 30 m, affect the morphometric characterization and topography derivatives. To reduce misregistration between the DEMs, spatial co-registration was performed and a RMSE of 0.48 pixel was achieved. Morphometric parameters such as slope, maximum curvature, minimum curvature and cross-sectional curvature are derived using a bivariate quadratic approximation on 90 m, 30 m and interpolated 30 m DEMs. Self Organizing Map (SOM) is used for the classification of morphometric parameters into ten exclusive and exhaustive classes. These classes were analyzed as morphometric features such as ridge, channel, crest line and planar for all data sets based on feature space (scatter plot), morphometric signatures and 3D inspection of the area. The map quality is analyzed by oblique views with contour lines overlaid. Using the X band DEM with 30 m grid as benchmark, a change detection technique was used to quantify differences in morphometric features and to assess the scale effect going from a 90 m (C-band) DEM to an interpolated 30 m DEM. The same procedure is used to study the effect of different resolutions on morphometric features. Morphometric parameters were computed by a moving window size 5 x 5 (corresponding to 450 m on the ground) over SRTM- 90 m. To cover the same ground area, a moving window size of 15 x 15 is used for the 30 m DEM. The change analysis showed the amount of resolution dependency of morphometric features. Overall, the results showed that the introduced method is very useful for identification of morphometric features based on SRTM resolution. Decreasing the grid size from 90 m to 30 m reveals considerably more detailed information emphasizing local conditions. Comparison between results from DEM-30 m as reference data set and interpolated 30 m, showed a rate of change of 31.5% which is negligible. About 17% of this rate correspond to classes with mean slope > 10°. Of the morphometric parameters, the cross sectional curvature is most sensitive to DEM resolution. Increasing spatial resolution reduces the main constrains for morphometric analysis with SRTM 90 m data, such as unrealistic features and isolated single elements in the output map. So in case of lack of high resolution data, the SRTM 90 m data could be interpolated and used for further geomorphic analysis. Copyright Springer Numéro de notice : A2010-302 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s10707-009-0085-4 Date de publication en ligne : 29/04/2009 En ligne : https://doi.org/10.1007/s10707-009-0085-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30496
in Geoinformatica > vol 14 n° 4 (October 2010) . - pp 405 - 424[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 057-2010041 RAB Revue Centre de documentation En réserve L003 Disponible Automatic detection of residential building using LIDAR data and multispectral imagery / M. Awrangjeb in ISPRS Journal of photogrammetry and remote sensing, vol 65 n° 5 (September - October 2010)
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Titre : Automatic detection of residential building using LIDAR data and multispectral imagery Type de document : Article/Communication Auteurs : M. Awrangjeb, Auteur ; M. Ravanbakhsh, Auteur ; Clive Simpson Fraser, Auteur Année de publication : 2010 Article en page(s) : pp 457 - 467 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] correction d'image
[Termes IGN] détection du bâti
[Termes IGN] données lidar
[Termes IGN] image multibande
[Termes IGN] masque
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] seuillage d'imageRésumé : (Auteur) This paper presents an automatic building detection technique using LIDAR data and multispectral imagery. Two masks are obtained from the LIDAR data: a ‘primary building mask’ and a ‘secondary building mask’. The primary building mask indicates the void areas where the laser does not reach below a certain height threshold. The secondary building mask indicates the filled areas, from where the laser reflects, above the same threshold. Line segments are extracted from around the void areas in the primary building mask. Line segments around trees are removed using the normalized difference vegetation index derived from the orthorectified multispectral images. The initial building positions are obtained based on the remaining line segments. The complete buildings are detected from their initial positions using the two masks and multispectral images in the YIQ colour system. It is experimentally shown that the proposed technique can successfully detect urban residential buildings, when assessed in terms of 15 indices including completeness, correctness and quality. Numéro de notice : A2010-448 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2010.06.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2010.06.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30641
in ISPRS Journal of photogrammetry and remote sensing > vol 65 n° 5 (September - October 2010) . - pp 457 - 467[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2010051 SL Revue Centre de documentation Revues en salle Disponible Comparison of matching algorithms for DSM generation in urban areas from ikonos imagery / A. Alobeid in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 9 (September 2010)
PermalinkDétection de dommages et évaluation des dégâts du réseau routier après un séisme, en utilisant des images QuickBird haute résolution / A. Haghighattalab in XYZ, n° 124 (septembre - novembre 2010)
PermalinkEmbedding spatial information into image content description for scene retrieval / Nguyen-Vu Hoang in Pattern recognition, vol 43 n° 9 (September 2010)
PermalinkGeometric feature extraction by a multimarked point process / Florent Lafarge in IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI, vol 32 n° 9 (September 2010)
PermalinkA pre-screened and normalized multiple endmember spectral mixture analysis [MESMA] for mapping impervious surface area in Lake Kasumigaura Basin, Japan / F. Yang in ISPRS Journal of photogrammetry and remote sensing, vol 65 n° 5 (September - October 2010)
PermalinkApplication of remote sensing and geographic information system in change detection of the Netravati and Gurpur river channels, Karnataka, India / A. Kumar in Geocarto international, vol 25 n° 5 (August 2010)
PermalinkRule-based classification of a very high resolution image in an urban environment using multispectral segmentation by cartographic data / M. Bouziani in IEEE Transactions on geoscience and remote sensing, vol 48 n° 8 (August 2010)
PermalinkSemisupervised one-class support vector machine for classification of remote sensing data / Jordi Munoz-Mari in IEEE Transactions on geoscience and remote sensing, vol 48 n° 8 (August 2010)
Permalink2D building change detection from high resolution satellite imagery: A two-step hierarchical method based on 3D invariant primitives / Nicolas Champion in Pattern recognition letters, vol 31 n° 10 (15 July 2010)
Permalinkvol 31 n° 13 - July /2010 - Special issue : Satellite observations of the Wenchuan earthquake of 12 may 2008 (Bulletin de International Journal of Remote Sensing IJRS) / Ranjit Singh
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