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Relating statistical characteristics of cross-polarized phase difference to speckle noise / Huimin Li in Journal of applied remote sensing, vol 9 (2015)
[article]
Titre : Relating statistical characteristics of cross-polarized phase difference to speckle noise Type de document : Article/Communication Auteurs : Huimin Li, Auteur ; Yunhua Wang, Auteur Année de publication : 2015 Article en page(s) : 8 p. Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] données polarimétriques
[Termes IGN] filtrage du bruit
[Termes IGN] image radar moirée
[Termes IGN] matrice de covariance
[Termes IGN] phase
[Termes IGN] polarimétrie radar
[Termes IGN] polarisation croiséeRésumé : (auteur) A qualitative relationship between the statistical behavior of cross-polarized phase difference ϕhvvh and dominant noise type is examined based on the polarimetric noise model proposed. The noise model focusing on the covariance matrix is able to separate the multiplicative noise which only affects the amplitude from the additive noise that alters both the amplitude and phase. In the case of low noise, the phase is not affected by the noise and ϕhvvh distribution is predicted to be centered at 0 deg in terms of reciprocity theorem. The case of strong noise is much more complicated as the dominant noise type plays an important role in the statistics of ϕhvvh. The phase over the area where multiplicative noise dominates is not altered, thus the ϕhvvh distribution is expected to have similar behaviors to the case of low noise. However, the dominant additive noise would significantly affect the phase so that an obvious deviation from 0 deg for ϕhvvh distribution is expected. Experiments with Radarsat-2 full polarimetric imageries further validate this qualitative relationship. Numéro de notice : A2015-101 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1117/1.JRS.9.090599 En ligne : http://remotesensing.spiedigitallibrary.org/article.aspx?articleid=2091528 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75392
in Journal of applied remote sensing > vol 9 (2015) . - 8 p.[article]Multi-view 3D circular target reconstruction with uncertainty analysis / Bahman Soheilian in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 (September 2014)
[article]
Titre : Multi-view 3D circular target reconstruction with uncertainty analysis Type de document : Article/Communication Auteurs : Bahman Soheilian , Auteur ; Mathieu Brédif , Auteur Année de publication : 2014 Conférence : PCV 2014, ISPRS Technical Commission 3 Symposium Photogrammetric Computer vision 05/09/2014 07/09/2014 Zurich Suisse OA ISPRS Annals Article en page(s) : pp 143 - 148 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] cible réfléchissante
[Termes IGN] cône
[Termes IGN] incertitude des données
[Termes IGN] matrice de covariance
[Termes IGN] modèle de Gauss-Helmert
[Termes IGN] programmation par contraintes
[Termes IGN] propagation d'erreur
[Termes IGN] reconstruction 3DRésumé : (auteur) The paper presents an algorithm for reconstruction of 3D circle from its apparition in n images. It supposes that camera poses are known up to an uncertainty. They will be considered as observations and will be refined during the reconstruction process. First, circle apparitions will be estimated in every individual image from a set of 2D points using a constrained optimization. Uncertainty of 2D points are propagated in 2D ellipse estimation and leads to covariance matrix of ellipse parameters. In 3D reconstruction process ellipse and camera pose parameters are considered as observations with known covariances. A minimal parametrization of 3D circle enables to model the projection of circle in image without any constraint. The reconstruction is performed by minimizing the length of observation residuals vector in a non linear Gauss-Helmert model. The output consists in parameters of the corresponding circle in 3D and their covariances. The results are presented on simulated data. Numéro de notice : A2014-774 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprsannals-II-3-143-2014 Date de publication en ligne : 07/09/2014 En ligne : http://dx.doi.org/10.5194/isprsannals-II-3-143-2014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78722
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol II-3 (September 2014) . - pp 143 - 148[article]Documents numériques
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Multi-view 3D circular target reconstruction with uncertainty analysisAdobe Acrobat PDF Novel Folded-PCA for improved feature extraction and data reduction with hyperspectral imaging and SAR in remote sensing / Jaime Zabalza in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)
[article]
Titre : Novel Folded-PCA for improved feature extraction and data reduction with hyperspectral imaging and SAR in remote sensing Type de document : Article/Communication Auteurs : Jaime Zabalza, Auteur ; Jinchang Ren, Auteur ; Mingqiang Yang, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp. 112 - 122 Langues : Anglais (eng) Descripteur : [Termes IGN] analyse en composantes principales
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image hyperspectrale
[Termes IGN] image radar
[Termes IGN] matrice de covarianceRésumé : As a widely used approach for feature extraction and data reduction, Principal Components Analysis (PCA) suffers from high computational cost, large memory requirement and low efficacy in dealing with large dimensional datasets such as Hyperspectral Imaging (HSI). Consequently, a novel Folded-PCA is proposed, where the spectral vector is folded into a matrix to allow the covariance matrix to be determined more efficiently. With this matrix-based representation, both global and local structures are extracted to provide additional information for data classification. Moreover, both the computational cost and the memory requirement have been significantly reduced. Using Support Vector Machine (SVM) for classification on two well-known HSI datasets and one Synthetic Aperture Radar (SAR) dataset in remote sensing, quantitative results are generated for objective evaluations. Comprehensive results have indicated that the proposed Folded-PCA approach not only outperforms the conventional PCA but also the baseline approach where the whole feature sets are used. Numéro de notice : A2014-330 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.04.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.04.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73697
in ISPRS Journal of photogrammetry and remote sensing > vol 93 (July 2014) . - pp. 112 - 122[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2014071 RAB Revue Centre de documentation En réserve L003 Disponible Maximum-likelihood estimation for multi-aspect multi-baseline SAR interferometry of urban areas / Michael Schmitt in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)
[article]
Titre : Maximum-likelihood estimation for multi-aspect multi-baseline SAR interferometry of urban areas Type de document : Article/Communication Auteurs : Michael Schmitt, Auteur ; Uwe Stilla, Auteur Année de publication : 2014 Article en page(s) : pp 68 - 77 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] image aérienne
[Termes IGN] image radar moirée
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] matrice de covariance
[Termes IGN] milieu urbain
[Termes IGN] modèle numérique de surface
[Termes IGN] Munich
[Termes IGN] reconstruction 3DRésumé : (Auteur) The reconstruction of digital surface models (DSMs) of urban areas from interferometric synthetic aperture radar (SAR) data is a challenging task. In particular the SAR inherent layover and shadowing effects need to be coped with by sophisticated processing strategies. In this paper, a maximum-likelihood estimation procedure for the reconstruction of DSMs from multi-aspect multi-baseline InSAR imagery is proposed. In this framework, redundant as well as contradicting observations are exploited in a statistically optimal way. The presented method, which is especially suited for single-pass SAR interferometers, is examined using test data consisting of experimental airborne millimeterwave SAR imagery. The achievable accuracy is evaluated by comparison to LiDAR-derived reference data. It is shown that the proposed estimation procedure performs better than a comparable non-statistical reconstruction method. Numéro de notice : A2014-013 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.10.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.10.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32918
in ISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 68 - 77[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2014011 RAB Revue Centre de documentation En réserve L003 Disponible Unmixing polarimetric radar images based on land cover type before target decomposition / Sébastien Giordano (2014)
Titre : Unmixing polarimetric radar images based on land cover type before target decomposition Type de document : Article/Communication Auteurs : Sébastien Giordano , Auteur ; Grégoire Mercier, Auteur ; Jean-Paul Rudant , Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2014 Conférence : IGARSS 2014, International Geoscience And Remote Sensing Symposium 13/07/2014 18/07/2014 Québec Québec - Canada Proceedings IEEE Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] image radar
[Termes IGN] matrice de covariance
[Termes IGN] polarimétrie radarRésumé : (auteur) A new method for unmixing radar polarimetric images with optical images is proposed. It was found that the polarimetric covariance matrix can be unmixed considering a linear model. As a result, this model is used to produce unmixed covariance matrices based on land cover types. We hope to prove that this unmixing of the polarimetric information produce greater information for land cover classification. Numéro de notice : C2014-043 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IGARSS.2014.6947055 Date de publication en ligne : 06/11/2014 En ligne : https://doi.org/10.1109/IGARSS.2014.6947055 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99588 Singular spectrum analysis for modeling seasonal signals from GPS time series / Q. Chen in Journal of geodynamics, vol 72 (December 2013)PermalinkFast error analysis of continuous GNSS observations with missing data / M.S. Bos in Journal of geodesy, vol 87 n° 4 (April 2013)PermalinkEstimation of mass change trends in the Earth’s system on the basis of GRACE satellite data, with application to Greenland / C. Siemes in Journal of geodesy, vol 87 n° 1 (January 2013)PermalinkRetrieval of phase history parameters from distributed scatterers in urban areas using very high resolution SAR data / Y. Wang in ISPRS Journal of photogrammetry and remote sensing, vol 73 (September 2012)PermalinkPermalinkEfficient estimation of variance and covariance components : A case study for GPS stochastic model evaluation / B. Li in IEEE Transactions on geoscience and remote sensing, vol 49 n° 1 Tome 1 (January 2011)PermalinkThe combination of GNSS-levelling data and gravimetric (quasi-) geoid heights in the presence of noise / R. Klees in Journal of geodesy, vol 84 n° 12 (December 2010)PermalinkFast GNSS ambiguity resolution as an ill-posed problem / Lard Erik Sjöberg in Journal of geodesy, vol 84 n° 11 (November 2010)PermalinkCombinaison linéaire et l'intérêt de la troisième fréquence pour le positionnement en double différence par GPS / L. Tabti in XYZ, n° 124 (septembre - novembre 2010)PermalinkApproximating covariance matrices estimated in multivariate models by estimated auto- and cross-covariances / Karl Rudolf Koch in Journal of geodesy, vol 84 n° 6 (June 2010)Permalink