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Spectral-spatial classification of hyperspectral images using wavelet transform and hidden Markov random fields / Elham Kordi Ghasrodashti in Geocarto international, vol 33 n° 8 (August 2018)
[article]
Titre : Spectral-spatial classification of hyperspectral images using wavelet transform and hidden Markov random fields Type de document : Article/Communication Auteurs : Elham Kordi Ghasrodashti, Auteur ; Mohammad Sadegh Helfroush, Auteur ; Habibollah Danyali, Auteur Année de publication : 2018 Article en page(s) : pp 771 - 790 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] champ aléatoire de Markov
[Termes IGN] image hyperspectrale
[Termes IGN] régularisation
[Termes IGN] transformation en ondelettesRésumé : (Auteur) This paper proposes a spectral–spatial method for classification of hyperspectral images. The proposed method, called SSC, consists of two steps. In the first step, to overcome the computation complexity, a wavelet-based classifier is designed. In the second step, to enhance the classification accuracy, a novel hidden Markov random field called NHMRF technique in spatial domain is suggested. In NHMRF, we convert two-dimensional energies of traditional hidden Markov random field to three-dimensional energies and then we apply edge preserving regularization terms on each two-dimensional energy of this cube. The class label of each test pixel is fixed based on minimum three-dimensional energy achieved by edge preserving regularization terms. Experimental results show that the classification accuracy of the proposed approach based on three-dimensional energies and edge preserving regularization terms is effectively improved in comparison with the state-of-the-art methods. Numéro de notice : A2018-335 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2017.1303087 Date de publication en ligne : 27/03/2017 En ligne : https://doi.org/10.1080/10106049.2017.1303087 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90533
in Geocarto international > vol 33 n° 8 (August 2018) . - pp 771 - 790[article]Parametric bootstrap estimators for hybrid inference in forest inventories / Mathieu Fortin in Forestry, an international journal of forest research, vol 91 n° 3 (July 2018)
[article]
Titre : Parametric bootstrap estimators for hybrid inference in forest inventories Type de document : Article/Communication Auteurs : Mathieu Fortin, Auteur ; Ruben Manso, Auteur ; Robert Schneider, Auteur Année de publication : 2018 Article en page(s) : pp 354 - 365 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Bootstrap (statistique)
[Termes IGN] complexité
[Termes IGN] erreur systématique
[Termes IGN] inférence statistique
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle stochastique
[Termes IGN] Québec (Canada)
[Termes IGN] variance
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) In forestry, the variable of interest is not always directly available from forest inventories. Consequently, practitioners have to rely on models to obtain predictions of this variable of interest. This context leads to hybrid inference, which is based on both the probability design and the model. Unfortunately, the current analytical hybrid estimators for the variance of the point estimator are mainly based on linear or nonlinear models and their use is limited when the model reaches a high level of complexity. An alternative consists of using a variance estimator based on resampling methods (Rubin, D. B. (1987). Multiple imputation for nonresponse surveys. John Wiley & Sons, Hoboken, New Jersey, USA). However, it turns out that a parametric bootstrap (BS) estimator of the variance can be biased in contexts of hybrid inference. In this study, we designed and tested a corrected BS estimator for the variance of the point estimator, which can easily be implemented as long as all of the stochastic components of the model can be properly simulated. Like previous estimators, this corrected variance estimator also makes it possible to distinguish the contribution of the sampling and the model to the variance of the point estimator. The results of three simulation studies of increasing complexity showed no evidence of bias for this corrected variance estimator, which clearly outperformed the BS variance estimator used in previous studies. Since the implementation of this corrected variance estimator is not much more complicated, we recommend its use in contexts of hybrid inference based on complex models. Numéro de notice : A2018-637 Affiliation des auteurs : non IGN Thématique : FORET/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/forestry/cpx048 Date de publication en ligne : 22/11/2017 En ligne : https://doi.org/10.1093/forestry/cpx048 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93246
in Forestry, an international journal of forest research > vol 91 n° 3 (July 2018) . - pp 354 - 365[article]Stochastic models in the DORIS position time series : estimates for IDS contribution to ITRF2014 / Anna Klos in Journal of geodesy, vol 92 n° 7 (July 2018)
[article]
Titre : Stochastic models in the DORIS position time series : estimates for IDS contribution to ITRF2014 Type de document : Article/Communication Auteurs : Anna Klos, Auteur ; Janusz Bogusz, Auteur ; Guilhem Moreaux, Auteur Année de publication : 2018 Article en page(s) : pp 743 - 763 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux
[Termes IGN] données DORIS
[Termes IGN] International Terrestrial Reference Frame
[Termes IGN] modèle stochastique
[Termes IGN] série temporelleRésumé : (Auteur) This paper focuses on the investigation of the deterministic and stochastic parts of the Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) weekly time series aligned to the newest release of ITRF2014. A set of 90 stations was divided into three groups depending on when the data were collected at an individual station. To reliably describe the DORIS time series, we employed a mathematical model that included the long-term nonlinear signal, linear trend, seasonal oscillations and a stochastic part, all being estimated with maximum likelihood estimation. We proved that the values of the parameters delivered for DORIS data are strictly correlated with the time span of the observations. The quality of the most recent data has significantly improved. Not only did the seasonal amplitudes decrease over the years, but also, and most importantly, the noise level and its type changed significantly. Among several tested models, the power-law process may be chosen as the preferred one for most of the DORIS data. Moreover, the preferred noise model has changed through the years from an autoregressive process to pure power-law noise with few stations characterised by a positive spectral index. For the latest observations, the medians of the velocity errors were equal to 0.3, 0.3 and 0.4 mm/year, respectively, for the North, East and Up components. In the best cases, a velocity uncertainty of DORIS sites of 0.1 mm/year is achievable when the appropriate coloured noise model is taken into consideration. Numéro de notice : A2018-454 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-017-1092-0 Date de publication en ligne : 30/11/2017 En ligne : https://doi.org/10.1007/s00190-017-1092-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91045
in Journal of geodesy > vol 92 n° 7 (July 2018) . - pp 743 - 763[article]Geodetic VLBI with an artificial radio source on the Moon : a simulation study / Grzegorz Klopotek in Journal of geodesy, vol 92 n° 5 (May 2018)
[article]
Titre : Geodetic VLBI with an artificial radio source on the Moon : a simulation study Type de document : Article/Communication Auteurs : Grzegorz Klopotek, Auteur ; Thomas Hobiger, Auteur ; Rüdiger Haas, Auteur Année de publication : 2018 Article en page(s) : pp 457 – 469 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] C++
[Termes IGN] émetteur
[Termes IGN] interférométrie à très grande base
[Termes IGN] Lune
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] modèle de simulation
[Termes IGN] modèle stochastique
[Termes IGN] simulationRésumé : (Auteur) We perform extensive simulations in order to assess the accuracy with which the position of a radio transmitter on the surface of the Moon can be determined by geodetic VLBI. We study how the quality and quantity of geodetic VLBI observations influence these position estimates and investigate how observations of such near-field objects affect classical geodetic parameters like VLBI station coordinates and Earth rotation parameters. Our studies are based on today’s global geodetic VLBI schedules as well as on those designed for the next-generation geodetic VLBI system. We use Monte Carlo simulations including realistic stochastic models of troposphere, station clocks, and observational noise. Our results indicate that it is possible to position a radio transmitter on the Moon using today’s geodetic VLBI with a two-dimensional horizontal accuracy of better than one meter. Moreover, we show that the next-generation geodetic VLBI has the potential to improve the two-dimensional accuracy to better than 5 cm. Thus, our results lay the base for novel observing concepts to improve both lunar research and geodetic VLBI. Numéro de notice : A2018-149 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-017-1072-4 Date de publication en ligne : 27/10/2017 En ligne : https://doi.org/10.1007/s00190-017-1072-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89760
in Journal of geodesy > vol 92 n° 5 (May 2018) . - pp 457 – 469[article]Contextual classification using photometry and elevation data for damage detection after an earthquake event / Ewelina Rupnik in European journal of remote sensing, vol 51 n° 1 (2018)
[article]
Titre : Contextual classification using photometry and elevation data for damage detection after an earthquake event Type de document : Article/Communication Auteurs : Ewelina Rupnik , Auteur ; Francesco Nex, Auteur ; Isabella Toschi, Auteur ; Fabio Remondino, Auteur Année de publication : 2018 Projets : 3-projet - voir note / Article en page(s) : pp 543 - 557 Note générale : bibliographie
This work was supported by RAPIDMAP, a CONCERT-Japan project, i.e. a European Union (EU) funded project in the International Cooperation Activities under the Capacities Programme the 7th Framework Programme for Research and Technology Development. https://cordis.europa.eu/project/id/266604/reportingLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] cartographie d'urgence
[Termes IGN] chaîne de traitement
[Termes IGN] champ aléatoire conditionnel
[Termes IGN] classification contextuelle
[Termes IGN] classification dirigée
[Termes IGN] classification non dirigée
[Termes IGN] détection de changement
[Termes IGN] dommage matériel
[Termes IGN] image aérienne
[Termes IGN] modèle numérique de surface
[Termes IGN] orthoimage
[Termes IGN] photométrie
[Termes IGN] prise en compte du contexte
[Termes IGN] zone urbaineRésumé : (auteur) This research presents a processing workflow to automatically find damaged building areas in an urban context. The input data requirements are high-resolution multi-view images, acquired from airborne platform. The elevations are derived from a dense surface model generated with photogrammetric methods. With the principal objective of rapid response in emergency situations, two different processing roadmaps are proposed, semi-supervised and unsupervised. Both of them follow a two-step workflow of building detection and building health estimation. Optionally, cadastral layers may serve as a-priori knowledge on building location. The semi-supervised approach involves a data training step, while the unsupervised approach exploits the similarities and dissimilarities between sets of features calculated over the detected buildings. The change detection task is formulated as a classification task defined over a conditional random field. The algorithms are evaluated using two datasets (Vexcel and Midas cameras) and results are compared with ground truth data and specific metrics. Numéro de notice : A2018-664 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/22797254.2018.1458584 Date de publication en ligne : 16/05/2018 En ligne : https://doi.org/10.1080/22797254.2018.1458584 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94250
in European journal of remote sensing > vol 51 n° 1 (2018) . - pp 543 - 557[article]Estimated location of the seafloor sources of marine natural oil seeps from sea surface outbreaks : A new "source path procedure" applied to the northern Gulf of Mexico / Zhour Najoui in Marine and Petroleum Geology, Vol 91 (March 2018)PermalinkCrop-rotation structured classification using multi-source sentinel images and LPIS for crop type mapping / Simon Bailly (2018)PermalinkMarkov random field for combined defogging and stereo reconstruction / Laurent Caraffa (2018)PermalinkLearning aggregated features and optimizing model for semantic labeling / Jianhua Wang in The Visual Computer, vol 33 n° 12 (December 2017)PermalinkSystematic error mitigation in multi-GNSS positioning based on semiparametric estimation / Wenkun Yu in Journal of geodesy, vol 91 n° 12 (December 2017)PermalinkAssessing the performance of multi-GNSS precise point positioning in Asia-Pacific region / X. Zhao in Survey review, vol 49 n° 354 (September 2017)PermalinkImpact of spatial correlations on the surface estimation based on terrestrial laser scanning / Tobias Jurek in Journal of applied geodesy, vol 11 n° 3 (September 2017)PermalinkA higher order conditional random field model for simultaneous classification of land cover and land use / Lena Albert in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)PermalinkRobust point cloud classification based on multi-level semantic relationships for urban scenes / Qing Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 129 (July 2017)PermalinkPerformance evaluation of land change simulation models using landscape metrics / Sadeq Dezhkam in Geocarto international, vol 32 n° 6 (June 2017)PermalinkAnalyse de séries temporelles d’images Sentinel et intégration de connaissances pour la classification en milieu agricole / Simon Bailly (2017)PermalinkComparison of belief propagation and graph-cut approaches for contextual classification of 3D LIDAR point cloud data / Loïc Landrieu (2017)PermalinkComputationally efficient hyperspectral data learning based on the doubly stochastic dirichlet process / Xing Sun in IEEE Transactions on geoscience and remote sensing, vol 55 n° 1 (January 2017)PermalinkHyperspectral image classification with canonical correlation forests / Junshi Xia in IEEE Transactions on geoscience and remote sensing, vol 55 n° 1 (January 2017)PermalinkPermalinkModèles géographiques avec le langage Mathematica / André Dauphiné (2017)PermalinkPré-segmentation pour la classification faiblement supervisée de scènes urbaines à partir de nuages de points 3D LIDAR / Stéphane Guinard (2017)PermalinkRandom-walker-based collaborative learning for hyperspectral image classification / Bin Sun in IEEE Transactions on geoscience and remote sensing, vol 55 n° 1 (January 2017)PermalinkWeakly supervised segmentation-aided classification of urban scenes from 3D LIDAR point clouds / Stéphane Guinard (2017)PermalinkDetermination of a terrestrial reference frame via Kalman filtering of very long baseline interferometry data / Benedikt Soja in Journal of geodesy, vol 90 n° 12 (December 2016)Permalink