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Spectral–spatial hyperspectral image classification via multiscale adaptive sparse representation / Leyuan Fang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 12 (December 2014)
[article]
Titre : Spectral–spatial hyperspectral image classification via multiscale adaptive sparse representation Type de document : Article/Communication Auteurs : Leyuan Fang, Auteur ; Shutao Li, Auteur ; Xudong Kang, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 7738 - 7749 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse multiéchelle
[Termes IGN] classification spectrale
[Termes IGN] image hyperspectrale
[Termes IGN] représentation parcimonieuseRésumé : (Auteur) Sparse representation has been demonstrated to be a powerful tool in classification of hyperspectral images (HSIs). The spatial context of an HSI can be exploited by first defining a local region for each test pixel and then jointly representing pixels within each region by a set of common training atoms (samples). However, the selection of the optimal region scale (size) for different HSIs with different types of structures is a nontrivial task. In this paper, considering that regions of different scales incorporate the complementary yet correlated information for classification, a multiscale adaptive sparse representation (MASR) model is proposed. The MASR effectively exploits spatial information at multiple scales via an adaptive sparse strategy. The adaptive sparse strategy not only restricts pixels from different scales to be represented by training atoms from a particular class but also allows the selected atoms for these pixels to be varied, thus providing an improved representation. Experiments on several real HSI data sets demonstrate the qualitative and quantitative superiority of the proposed MASR algorithm when compared to several well-known classifiers. Numéro de notice : A2014-639 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2317499 En ligne : https://doi.org/10.1109/TGRS.2014.2317499 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75076
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 12 (December 2014) . - pp 7738 - 7749[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2014121 RAB Revue Centre de documentation En réserve L003 Disponible Assessment of observing time-variable gravity from GOCE GPS and accelerometer observations / Pieter N.A.M. Visser in Journal of geodesy, vol 88 n° 11 (November 2014)
[article]
Titre : Assessment of observing time-variable gravity from GOCE GPS and accelerometer observations Type de document : Article/Communication Auteurs : Pieter N.A.M. Visser, Auteur ; W. Van der Wal, Auteur ; E.J.O. Schrama, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 1029 - 1046 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] données GOCE
[Termes IGN] données GPS
[Termes IGN] effet atmosphérique
[Termes IGN] gravimétrie spatiale
[Termes IGN] orbite
[Termes IGN] variableRésumé : (Auteur) An assessment has been made of the possibility to estimate time-variable gravity from GPS-derived orbit perturbations and common-mode accelerometer observations of ESA’s GOCE Earth Explorer. A number of 20-day time series of Earth’s global long-wavelength gravity field have been derived for the period November 2009 to November 2012 using different parameter setups and estimation techniques. These techniques include a conventional approach where for each period, one set of gravity coefficients is estimated, either excluding or including empirical accelerations, and the so-called Wiese approach where higher frequency coefficients are estimated for the very long wavelengths. A principal component analysis of especially the time series of gravity field coefficients obtained by the Wiese approach and the conventional approach with empirical accelerations reveals an annual signal. When fitting this annual signal directly through the time series, the sine component (maximum in spring) displays features that are similar to well-known continental hydrological mass changes for the low latitude areas, such as mass variations in the Amazon basin, Africa and Australia for spatial scales down to 1,500 km. The cosine component (maximum in winter), however, displays large signals that can not be attributed to actual mass variations in the Earth system. The estimated gravity field changes from GOCE orbit perturbations are likely affected by missing GPS observations in case of high ionospheric perturbations during periods of increased solar activity, which is minimal in Summer and maximal towards the end of autumn. Numéro de notice : A2014-563 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-014-0741-9 Date de publication en ligne : 27/06/2014 En ligne : https://doi.org/10.1007/s00190-014-0741-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74749
in Journal of geodesy > vol 88 n° 11 (November 2014) . - pp 1029 - 1046[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 266-2014111 SL Revue Centre de documentation Revues en salle Disponible Hyperspectral unmixing with [lq] regularization / Jakob Sigurdsson in IEEE Transactions on geoscience and remote sensing, vol 52 n° 11 tome 1 (November 2014)
[article]
Titre : Hyperspectral unmixing with [lq] regularization Type de document : Article/Communication Auteurs : Jakob Sigurdsson, Auteur ; Magnus Orn Ulfarsson, Auteur ; Johannes R. Sveinsson, Auteur Année de publication : 2014 Article en page(s) : pp 6793 - 6806 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] image hyperspectrale
[Termes IGN] traitement du signalRésumé : (Auteur) Hyperspectral unmixing is an important technique for analyzing remote sensing images. In this paper, we consider and examine the ℓq, 0 ≤ q ≤ 1 penalty on the abundances for promoting sparse unmixing of hyperspectral data. We also apply a first-order roughness penalty to promote piecewise smooth end-members. A novel iterative algorithm for simultaneously estimating the end-members and the abundances is developed and tested both on simulated and two real hyperspectral data sets. We present an extensive simulation study where we vary both the SNR and the sparsity of the simulated data and identify the model parameters that minimize the reconstruction errors and the spectral angle distance. We show that choosing 0 ≤ q Numéro de notice : A2014-540 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2303155 En ligne : https://doi.org/10.1109/TGRS.2014.2303155 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74157
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 11 tome 1 (November 2014) . - pp 6793 - 6806[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2014111A RAB Revue Centre de documentation En réserve L003 Disponible A new sparse source separation-based classification approach / M.A. Loghmari in IEEE Transactions on geoscience and remote sensing, vol 52 n° 11 tome 1 (November 2014)
[article]
Titre : A new sparse source separation-based classification approach Type de document : Article/Communication Auteurs : M.A. Loghmari, Auteur ; Mohamed Saber Naceur, Auteur ; Mohamed-Rached Boussema, Auteur Année de publication : 2014 Article en page(s) : pp 6924 - 6936 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification
[Termes IGN] classification non dirigée
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] séparation aveugle de source
[Termes IGN] traitement du signalRésumé : (Auteur) In many geoscience applications, we have to convert remotely sensed images to ground cover maps. Numerous approaches to extract ground cover information have been developed. Recently, blind source separation (BSS) of remote-sensing data has received significant attention due to its suitability to recover sources when no information is available about the scanned zone, hence the term blind. In the remote-sensing context, associating each source to a significant land cover theme is difficult and constitutes the real challenge of this paper. Many authors have pointed out that BSS is overwhelmingly a question of contrast and diversity. This reasoning motivates this work which takes advantage of both decorrelation and sparsity to propose a two-level novel approach to separate our different land covers called sources. The first separation stage is based on second-order statistics or decorrelation. It gives a suitable representation of the remote-sensing images. However, decorrelation is a natural way of differentiating statistically between sources but is unable to identify and extract finer features with physical meaning. The aim of the second separation stage is to overcome this problem by an increasingly popular and powerful assumption which is the sparse representation. The last leads to good separation because most of the energy in the defined basis, at any time instant, belongs to a single source. This allows the extraction of physical features and the capture of image essential structures. The innovative aspect of this study concerns the development of a new image classification approach that integrates the BSS at the feature extraction level to provide the most relevant sources from remotely sensed images. It can be viewed as an unsupervised classification method. The second-order separation process is used as a preprocessing step to remove the interband correlation which sometimes brings ill effect to image classification. However, the second-order process is unable to uncover the underlying sources. The basic idea behind our approach is that heterogeneous multichannel data provide sparse spectral signatures in addition to sparse spatial morphologies in specified dictionaries. Hence, sparse modeling can be used to disentangle the land covers from observed mixtures. From the sparse representation, the data space is transformed into a feature space composed of mutually exclusive classes. Finally, we will merge these classes at the decision level in order to enhance the semantic capability and the reliability of land cover classification. The effectiveness of the proposed approach was demonstrated by operating two experiments to study respectively the source separation and the image classification capability of the developed approach. The different results on remote-sensing images illustrate the good performance of the new sparse approach and its robustness to noise. These experiments show that the sparse representation enhances the separation quality and allows extracting more easily the essential structures of the scanned zone. The proposed approach offers an interesting solution to the classification process with limited knowledge of ground truth. Numéro de notice : A2014-542 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2305724 En ligne : https://doi.org/10.1109/TGRS.2014.2305724 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74159
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 11 tome 1 (November 2014) . - pp 6924 - 6936[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2014111A RAB Revue Centre de documentation En réserve L003 Disponible Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices / L. Ji in ISPRS Journal of photogrammetry and remote sensing, vol 96 (October 2014)
[article]
Titre : Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices Type de document : Article/Communication Auteurs : L. Ji, Auteur ; Li Zhang, Auteur ; Jennifer Rover, Auteur Année de publication : 2014 Article en page(s) : pp 20 - 47 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal
[Termes IGN] bruit (théorie du signal)
[Termes IGN] estimation statistique
[Termes IGN] géostatistique
[Termes IGN] indice de végétationRésumé : (Auteur) In the past 40 years, many spectral vegetation indices have been developed to quantify vegetation biophysical parameters. An ideal vegetation index should contain the maximum level of signal related to specific biophysical characteristics and the minimum level of noise such as background soil influences and atmospheric effects. However, accurate quantification of signal and noise in a vegetation index remains a challenge, because it requires a large number of field measurements or laboratory experiments. In this study, we applied a geostatistical method to estimate signal-to-noise ratio (S/N) for spectral vegetation indices. Based on the sample semivariogram of vegetation index images, we used the standardized noise to quantify the noise component of vegetation indices. In a case study in the grasslands and shrublands of the western United States, we demonstrated the geostatistical method for evaluating S/N for a series of soil-adjusted vegetation indices derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The soil-adjusted vegetation indices were found to have higher S/N values than the traditional normalized difference vegetation index (NDVI) and simple ratio (SR) in the sparsely vegetated areas. This study shows that the proposed geostatistical analysis can constitute an efficient technique for estimating signal and noise components in vegetation indices. Numéro de notice : A2014-382 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.06.013 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.06.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73809
in ISPRS Journal of photogrammetry and remote sensing > vol 96 (October 2014) . - pp 20 - 47[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2014101 RAB Revue Centre de documentation En réserve L003 Disponible A Realistic and Easy-to-Implement Weighting Model for GPS Phase Observations / Xiaoguang Luo in IEEE Transactions on geoscience and remote sensing, vol 52 n° 10 tome 1 (October 2014)PermalinkSubspace-based technique for speckle noise reduction in SAR images / Norashikin Yahya in IEEE Transactions on geoscience and remote sensing, vol 52 n° 10 tome 1 (October 2014)Permalink3-Pol polarimetric weather measurements with agile-beam phased-array radars / Verónica Santalla del Rio in IEEE Transactions on geoscience and remote sensing, vol 52 n° 9 Tome 2 (September 2014)PermalinkLa forêt française, l'agroforesterie et la filière bois : quel potentiel d'atténuation climatique à moyen et long terme ? / Michel de Galbert in Revue forestière française, vol 66 n° 5 (septembre - octobre 2014)PermalinkA novel rapid SAR simulator based on equivalent scatterers for three-dimensional forest canopies / Tao Zeng in IEEE Transactions on geoscience and remote sensing, vol 52 n° 9 Tome 1 (September 2014)PermalinkTraitement de données Thematic Mapper pour la cartographie multi temporelle du plateau sous-marin autour des îles Kerkennah (Tunisie) / Rim Katlane in Photo interprétation, European journal of applied remote sensing, vol 50 n° 3 - 4 (septembre 2014)PermalinkLimnimétrie par réflectrométrie GNSS à faible coût / Eduardo Rodrigues in Géomatique suisse, vol 112 n° 8 (août 2014)PermalinkLimnimétrie par réflectométrie GNSS à faible coût / Eduardo Rodrigues in XYZ, n° 139 (juin - août 2014)PermalinkReal-time deformation monitoring by a wireless network of low-cost GPS / Lionel Benoit in Journal of applied geodesy, vol 8 n° 2 (June 2014)PermalinkThe European way: Performance of the Galileo single-frequency ionospheric correction during in-orbit validation / Roberto Prieto-Cerdeira in GPS world, vol 25 n° 6 (June 2014)PermalinkApplication of SWACI products as ionospheric correction for single-point positioning: a comparative study / David Minkwitz in Journal of geodesy, vol 88 n° 5 (May 2014)PermalinkHyperspectral image denoising with a spatial–spectral view fusion strategy / Qiangqiang Yuan in IEEE Transactions on geoscience and remote sensing, vol 52 n° 5 tome 1 (May 2014)PermalinkImpact of signal contamination on the adaptive detection performance of local hyperspectral anomalies / Stefania Matteoli in IEEE Transactions on geoscience and remote sensing, vol 52 n° 4 (April 2014)PermalinkAnalyse des séries temporelles de coordonnées des sites multi-techniques (SLR, VLBI, DORIS et GPS) / Bachir Gourine in Bulletin des sciences géographiques, n° 29 (janvier - juin 2014)PermalinkBenchmarking framework for SAR despeckling / Gerardo Di Martino in IEEE Transactions on geoscience and remote sensing, vol 52 n° 3 (March 2014)PermalinkWater vapor probabilistic retrieval using GNSS signals / Andrea Antonini in IEEE Transactions on geoscience and remote sensing, vol 52 n° 3 (March 2014)PermalinkA better place / Jane Khodos in GEO: Geoconnexion international, vol 13 n° 2 (february 2014)PermalinkBlind speckle decorrelation for SAR image despeckling / Alessandro Lapini in IEEE Transactions on geoscience and remote sensing, vol 52 n° 2 (February 2014)PermalinkEffects of atmospheric stability and wind fetch on microwave sea echoes / Yunhua Wang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 2 (February 2014)PermalinkGNSS ambiguity resolution with controllable failure rate for long baseline network RTK / Bofeng Li in Journal of geodesy, vol 88 n° 2 (February 2014)Permalink