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Intensity-driven-adaptive-neighbourhood technique for PolSAR parameters estimation / Gabriel Vasile (2005)
Titre : Intensity-driven-adaptive-neighbourhood technique for PolSAR parameters estimation Type de document : Article/Communication Auteurs : Gabriel Vasile, Auteur ; Emmanuel Trouvé, Auteur ; M. Ciuc, Auteur ; et al., Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2005 Conférence : IGARSS 2005, International Geoscience And Remote Sensing Symposium 29/07/2005 Séoul Corée du Sud Proceedings IEEE Importance : 4 p. Format : 21 x 30 cm Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] cohérence des données
[Termes IGN] données polarimétriques
[Termes IGN] image radar moirée
[Termes IGN] polarimétrie radarRésumé : (Auteur) In this paper, a new method to estimate polarimetric coherency matrices and derive associated parameters is presented. For each pixel of the data set, an adaptive neighborhood is computed by a region growing technique driven exclusively by the intensity images. The three intensity images of the POLSAR acquisition are fused in the region growing process to ensure the stationarity hypothesis of the derived statistical population. Then, all pixels within the obtained adaptive neighborhood are, either complex averaged or estimated by the locally linear minimum mean{squared error (LLMMSE), to yield a feature preserving reliable estimate of the polarimetric coherency matrix. The target entropy{alpha{anisotropy decomposition is applied on the derived polarimetric coherency matrix. Using this decomposition, unsupervised classification for land applications by an iterative algorithm based on a complex Wishart density function is employed. The method has been tested on airborne polarimetric synthetic aperture radar images (Northumberland Strait costal area { Canadian Space Agency). Numéro de notice : 13578 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IGARSS.2005.1526020 Date de publication en ligne : 14/11/2005 En ligne : https://doi.org/10.1109/IGARSS.2005.1526020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=64264 Discrimination potential of X-band polarimetric SAR data / Nicolas Baghdadi in International Journal of Remote Sensing IJRS, vol 25 n° 22 (November 2004)
[article]
Titre : Discrimination potential of X-band polarimetric SAR data Type de document : Article/Communication Auteurs : Nicolas Baghdadi, Auteur ; N. Holah, Auteur ; P. Dubois-Fernandez, Auteur ; L. Prevot, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 4933 - 4943 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse discriminante
[Termes IGN] anisotropie
[Termes IGN] Avignon
[Termes IGN] bande X
[Termes IGN] données polarimétriques
[Termes IGN] image radar moirée
[Termes IGN] image RAMSES
[Termes IGN] Radar Aéroporté Multi-Spectral d'Etude des Signatures
[Termes IGN] sol nuRésumé : (Auteur) In anticipation of X-band polarimetric Synthetic Aperture Radar (SAR) data from future sensors, we investigated the potential of X-band fully polarimetric data for discriminating between the principal classes present in a study site near Avignon, France. Decomposition and analysis techniques have been applied to a dataset acquired by the ONERA airborne RAMSES (Radar Aéroporté Multi-Spectral d'Etude des Signatures) SAR. Results show that X-band provides some discrimination capability. The polarimetric parameters, entropy and Ü-angle, show clearly that these signature classes are grouped into five clusters corresponding to physical scattering characteristics. The introduction of the anisotropy parameter does not increase our ability to distinguish between different classes whose clusters are in the same entropy/Ü-angle zone. The correlation observed between the radar signal and the surface roughness over bare soils is very low. Numéro de notice : A2004-488 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160412231269652 En ligne : https://doi.org/10.1080/01431160412231269652 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27006
in International Journal of Remote Sensing IJRS > vol 25 n° 22 (November 2004) . - pp 4933 - 4943[article]Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 080-04201 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Fully polarimetric airborne SAR and ERS SAR observations of snow: implications for selection of Envisat ASAR modes / T. Guneriussen in International Journal of Remote Sensing IJRS, vol 24 n° 19 (October 2003)
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Titre : Fully polarimetric airborne SAR and ERS SAR observations of snow: implications for selection of Envisat ASAR modes Type de document : Article/Communication Auteurs : T. Guneriussen, Auteur ; H. Johnsen, Auteur Année de publication : 2003 Article en page(s) : pp 3839 - 3854 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] atmosphère terrestre
[Termes IGN] bande C
[Termes IGN] bande L
[Termes IGN] données polarimétriques
[Termes IGN] glace
[Termes IGN] image EMISAR
[Termes IGN] image Envisat-ASAR
[Termes IGN] image ERS-SAR
[Termes IGN] manteau neigeux
[Termes IGN] montagne
[Termes IGN] neige
[Termes IGN] polarimétrie radarRésumé : (Auteur) Snow cover has a substantial impact on processes involved in the interaction between atmosphere and surface, and the knowledge of snow parameters is important in both climatology and weather forecasting. With the upcoming launch of Advanced Synthetic Aperture Radar (ASAR) instruments on Envisat, enhanced snow-mapping capabilities are foreseen. In this paper fully polarimetric C- and L-band airborne SAR data, ERS SAR and auxiliary data from various snow conditions in mountainous areas are analysed in order to determine the optimum ASAR modes for snow monitoring. The data used in this study are from the Norwegian part of the snow and ice experiment within the European Multi-sensor Airborne Campaign (EMAC'95) acquired in the Kongsfjellet area, located in Norway, 66°N, 14°E. Fully polarimetric C- and L-band SAR data from ElectroMagnetic Institute SAR (EMISAR), an airborne instrument operated by the Danish Center for Remote Sensing (DCR), were acquired in March, May, and July 1995. In addition, several ERS SAR, airborne photos, field and auxiliary data were acquired.
A larger separation between wet snow and bare ground in EMISAR C-VV polarisation data was found at high incidence angle (55°) compared to lower incidence angle (45°). Crosspolarized observations from bare ground, dry and wet snow in the incidence angle range 35° to 65° are below the specified Envisat ASAR noise floor of -20-22 dB. The backscattering angular dependency for wet snow and bare ground derived from EMISAR C-VV and ERS SAR data corresponds well, and agrees to some extent with volume and surface scattering model results. The C-band is more sensitive to variation in snow properties than the L-band.Numéro de notice : A2003-282 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/0143116021000053319 En ligne : https://doi.org/10.1080/0143116021000053319 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22577
in International Journal of Remote Sensing IJRS > vol 24 n° 19 (October 2003) . - pp 3839 - 3854[article]Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 080-03191 RAB Revue Centre de documentation En réserve L003 Exclu du prêt The use of fully polarimetric information for the fuzzy neural classification of SAR images / C.T. Chen in IEEE Transactions on geoscience and remote sensing, vol 41 n° 9 (September 2003)
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Titre : The use of fully polarimetric information for the fuzzy neural classification of SAR images Type de document : Article/Communication Auteurs : C.T. Chen, Auteur ; K.S. Chen, Auteur ; Jong-Sen Lee, Auteur Année de publication : 2003 Article en page(s) : pp 2089 - 2100 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] classification floue
[Termes IGN] classification par réseau neuronal
[Termes IGN] données polarimétriques
[Termes IGN] image AIRSAR
[Termes IGN] matrice de covariance
[Termes IGN] rétrodiffusion
[Termes IGN] utilisation du sol
[Termes IGN] vectorisationRésumé : (Auteur) This paper presents a method, based on a fuzzy neural network, that uses fully polarimetric information for terrain and land-use classification of synthetic aperture radar (SAR) image. The proposed approach makes use of statistical properties of polarimetric data, and takes advantage of a fuzzy neural network. A distance measure, based on a complex Wishart distribution, is applied using the fuzzy c-means clustering algorithm, and the clustering result is then incorporated into the neural network. Instead of preselecting the polarization channels to form a feature vector, all elements of the polarimetric covariance matrix serve as the target feature vector as inputs to the neural network. It is thus expected that the neural network will include fully polarimetric backscattering information for image classification. With the generalization, adaptation, and other capabilities of the neural network, information contained in the covariance matrix, such as the amplitude, the phase difference, the degree of polarization, etc., can be fully explored. A test image, acquired by the Jet Propulsion Laboratory Airborne SAR (AIRSAR) system, is used to demonstrate the advantages of the proposed method. It is shown that the proposed approach can greatly enhance the adaptability and the flexibility giving fully polarimetric SAR for terrain cover classification. The integration of fuzzy c-means (FCM) and fast generalization dynamic learning neural network (DLNN) capabilities makes the proposed algorithm an attractive and alternative method for polarimetric SAR classification. Numéro de notice : A2003-255 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2003.813494 En ligne : https://doi.org/10.1109/TGRS.2003.813494 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22550
in IEEE Transactions on geoscience and remote sensing > vol 41 n° 9 (September 2003) . - pp 2089 - 2100[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-03091 RAB Revue Centre de documentation En réserve L003 Disponible Radar imaging of moving targets in foliage using multifrequency multiaperture polarimetric SAR / G. Wang in IEEE Transactions on geoscience and remote sensing, vol 41 n° 8 (August 2003)
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Titre : Radar imaging of moving targets in foliage using multifrequency multiaperture polarimetric SAR Type de document : Article/Communication Auteurs : G. Wang, Auteur ; X.G. Xia, Auteur ; V. Chen, Auteur Année de publication : 2003 Article en page(s) : pp 1755 - 1764 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] données polarimétriques
[Termes IGN] feuille (végétation)
[Termes IGN] forêt
[Termes IGN] image radar moirée
[Termes IGN] objet mobile
[Termes IGN] polarimétrie radar
[Termes IGN] polarisationRésumé : (Auteur) Because of the low signal-to-clutter ratio, it is a difficult problem to detect and image moving targets in foliage. In this paper, a multifrequency multiaperture polarimetric synthetic aperture radar (MFMA POLSAR) system is proposed for imaging of moving targets in foliage. The MFMA POLSAR extends the multifrequency antenna array SAR (MFSAR) system to multiple the polarizations. Full polarization is used in MFMA POLSAR to achieve an optimal polarization adaptive to the environment such that the images obtained by different apertures are of the best coherence that is used to obtain the highest accuracy of the phase estimation. It is also shown that the MFMA POLSAR cannot only accurately locate both the slow and the fast moving targets but also reveal moving targets in foliage. Numéro de notice : A2003-277 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2003.813501 En ligne : https://doi.org/10.1109/TGRS.2003.813501 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22572
in IEEE Transactions on geoscience and remote sensing > vol 41 n° 8 (August 2003) . - pp 1755 - 1764[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-03081 RAB Revue Centre de documentation En réserve L003 Disponible Incidence angle dependence of the statistical properties of C-band HH-polarization backscattering signatures of the Baltic sea ice / Marko P. Mäkynen in IEEE Transactions on geoscience and remote sensing, vol 40 n° 12 (December 2002)PermalinkOn the estimation of radar polarization orientation shifts induced by terrain slopes / Jong-Sen Lee in IEEE Transactions on geoscience and remote sensing, vol 40 n° 1 (January 2002)PermalinkFiltrage du speckle dans les images radar à synthèse d'ouverture polarimétriques et classification supervisée multi-source / Franck Sery (1997)PermalinkMesures physiques et signatures en télédétection : 5ème Colloque International, Courchevel, France, 14-18 janvier 1991, Tome 1. Actes / J.J. Hunt (1991)PermalinkMesures physiques et signatures en télédétection : 5ème Colloque International, Courchevel, France, 14-18 janvier 1991, Tome 2. Actes / J.J. Hunt (1991)PermalinkRadar polarimetry for geoscience applications / F.T. Ulaby (1990)PermalinkPhotopolarimetric observations of aerosols and clouds from balloon / J.L. Deuze in Remote sensing of environment, vol 29 n° 2 (01/08/1989)Permalink