IEEE Transactions on geoscience and remote sensing / IEEE Geoscience and remote sensing society (Etats-Unis) . vol 53 n° 4Paru le : 01/04/2015 |
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Ajouter le résultat dans votre panierMapping aboveground biomass in northern japanese forests using the ALOS PRISM digital surface model / Takeshi Motohka in IEEE Transactions on geoscience and remote sensing, vol 53 n° 4 (April 2015)
[article]
Titre : Mapping aboveground biomass in northern japanese forests using the ALOS PRISM digital surface model Type de document : Article/Communication Auteurs : Takeshi Motohka, Auteur ; Toshiya Yoshida, Auteur ; Hideaki Shibata, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 1683 - 1691 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biomasse
[Termes IGN] évaluation des données
[Termes IGN] forêt
[Termes IGN] hauteur des arbres
[Termes IGN] image ALOS-PRISM
[Termes IGN] Japon
[Termes IGN] modèle numérique de sursolRésumé : (Auteur) We tested the performance of the stereo observations of the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) onboard the Advanced Land Observing Satellite (ALOS) in the mapping of forest aboveground biomass (AGB) in Japan. Digital canopy height models (DCHMs), which are differences between PRISM digital surface models and surveying-based digital terrain models (DTMs), were compared to in situ AGB measurements of several forest types (number of stands: 28; average stand size: 0.54 ha; stand size range: 0.25-3.00 ha). DCHM values exhibited a significant correlation with AGB (r = 0.66-0.87; five different DCHMs), and the root-mean-square error and bias of the regression model evaluated by the leave-one-out cross-validation were 37.2-57.8t/ha(22.1%-32.6%) and-0.11-1.89 t/ha, respectively. There was no saturation in the relationship between DCHM and AGB (AGB range: 19-332 t/ha). The correlations between DCHM and mean canopy height (r = 0.17-0.52) and between DCHM and Lorey's height (r = 0.26-0.66) were weaker than the correlation between DCHM and AGB. The PRISM AGB distribution estimated by the regression model was consistent with a tree density map produced from aerial photos. Comparison to Phased Array-type L-band Synthetic Aperture Radar (PALSAR) data showed that the PRISM DCHMs can estimate high AGB over the saturation level of PALSAR backscattering coefficient, i.e., 100-200 t/ha. The results described here demonstrate that the PRISM DCHMs are capable of wall-to-wall AGB estimation at 50-m resolution. This approach will be useful for improving the performance of satellite-based AGB estimation when an accurate DTM is available. Numéro de notice : A2015-169 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2346531 En ligne : https://doi.org/10.1109/TGRS.2014.2346531 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75884
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 4 (April 2015) . - pp 1683 - 1691[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015041 RAB Revue Centre de documentation En réserve L003 Disponible A technique for simultaneous visualization and segmentation of hyperspectral data / Abhimitra Meka in IEEE Transactions on geoscience and remote sensing, vol 53 n° 4 (April 2015)
[article]
Titre : A technique for simultaneous visualization and segmentation of hyperspectral data Type de document : Article/Communication Auteurs : Abhimitra Meka, Auteur ; Subhasis Chaudhuri, Auteur Année de publication : 2015 Article en page(s) : pp 1707 - 1717 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] image hyperspectrale
[Termes IGN] optimisation (mathématiques)
[Termes IGN] redondance de données
[Termes IGN] segmentation d'image
[Termes IGN] visualisation simultanéeRésumé : (Auteur) In this paper, we propose an optimization-based method for simultaneous fusion and unsupervised segmentation of hyperspectral remote sensing images by exploiting redundancy in the data. The hyperspectral data set is visualized as a single image obtained by weighted addition of all spectral points at each pixel location in the data set. The weights are optimized to improve those statistical characteristics of the fused image, which invoke an enhanced response from a human observer. A piecewise-constant smoothness constraint is imposed on the weights instead of the fused image by minimization of its 3-D total-variation norm, thus preventing the fused image from blurring. The optimal recovery of the weight matrix additionally provides useful information in segmenting the hyperspectral data set spatially. We provide ample experimental results to substantiate the usefulness of the proposed method. Numéro de notice : A2015-170 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2346653 Date de publication en ligne : 04/09/2014 En ligne : https://doi.org/04/09/201410.1109/TGRS.2014.2346653 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75886
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 4 (April 2015) . - pp 1707 - 1717[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015041 RAB Revue Centre de documentation En réserve L003 Disponible Active learning with gaussian process classifier for hyperspectral image classification / Shujing Sun in IEEE Transactions on geoscience and remote sensing, vol 53 n° 4 (April 2015)
[article]
Titre : Active learning with gaussian process classifier for hyperspectral image classification Type de document : Article/Communication Auteurs : Shujing Sun, Auteur ; Ping Zhong, Auteur ; Huaitie Xiao, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 1746 - 1760 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage automatique
[Termes IGN] classification bayesienne
[Termes IGN] image hyperspectraleRésumé : (Auteur) Gaussian process (GP) classifiers represent a powerful and interesting theoretical framework for the Bayesian classification of hyperspectral images. However, the collection of labeled samples is time consuming and costly for hyperspectral data, and the training samples available are often not enough for an adequate learning of the GP classifier. Moreover, the computational cost of performing inference using GP classifiers scales cubically with the size of the training set. To address the limitations of GP classifiers for hyperspectral image classification, reducing the label cost and keeping the training set in a moderate size, this paper introduces an active learning (AL) strategy to collect the most informative training samples for manual labeling. First, we propose three new AL heuristics based on the probabilistic output of GP classifiers aimed at actively selecting the most uncertain and confusing candidate samples from the unlabeled data. Moreover, we develop an incremental model updating scheme to avoid the repeated training of the GP classifiers during the AL process. The proposed approaches are tested on the classification of two realworld hyperspectral data. Comparison with random sampling method reveals a better accuracy gain and faster convergence with the number of queries, and comparison with recent active learning approaches shows a competitive performance. Experimental results also verified the efficiency of the incremental model updating scheme. Numéro de notice : A2015-171 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2347343 Date de publication en ligne : 29/08/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2347343 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75887
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 4 (April 2015) . - pp 1746 - 1760[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015041 RAB Revue Centre de documentation En réserve L003 Disponible A physics-based unmixing method to estimate subpixel temperatures on mixed pixels / Manuel Cubero-Castan in IEEE Transactions on geoscience and remote sensing, vol 53 n° 4 (April 2015)
[article]
Titre : A physics-based unmixing method to estimate subpixel temperatures on mixed pixels Type de document : Article/Communication Auteurs : Manuel Cubero-Castan, Auteur ; Jocelyn Chanussot, Auteur ; Véronique Achard, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 1894 - 1906 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse linéaire des mélanges spectraux
[Termes IGN] emissivité
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] image TASI
[Termes IGN] méthode des moindres carrés
[Termes IGN] rayonnement infrarouge thermique
[Termes IGN] température de luminanceRésumé : (Auteur) This paper presents a new algorithm for the analysis of linear spectral mixtures in the thermal infrared domain, with the goal to jointly estimate the abundance and the subpixel temperature in a mixed pixel, i.e., to estimate the relative proportion and the temperature of each material composing the mixed pixel. This novel approach is a two-step procedure. First, it estimates the emissivity and the temperature over pure pixels using the standard temperature and emissivity separation (TES) algorithm. Second, it estimates the abundance and the subpixel temperature using a new unmixing physics-based model, called Thermal Remote sensing Unmixing for Subpixel Temperature (TRUST). This model is based on an estimator of the subpixel temperature obtained by linearizing the black body law around the mean temperature of each material. The abundance is then retrieved by minimizing the reconstruction error with the estimation of the subpixel temperatures. The TRUST method is benchmarked on simulated scenes against the fully constrained least squares unmixing applied on the radiance and on the estimation of surface emissivity using the TES algorithm. The TRUST method shows better results on pure and mixed pixels composed of two materials. TRUST also shows promising results when applied on thermal hyperspectral data acquired with the Thermal Airborne Spectrographic Imager during the Detection in Urban scenario using Combined Airborne imaging Sensors campaign and estimates coherent localization of mixed-pixel areas. Numéro de notice : A2015-172 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2350771 Date de publication en ligne : 15/09/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2350771 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75890
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 4 (April 2015) . - pp 1894 - 1906[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015041 RAB Revue Centre de documentation En réserve L003 Disponible Linear spectral mixture analysis via multiple-kernel learning for hyperspectral image classification / Keng-Hao Liu in IEEE Transactions on geoscience and remote sensing, vol 53 n° 4 (April 2015)
[article]
Titre : Linear spectral mixture analysis via multiple-kernel learning for hyperspectral image classification Type de document : Article/Communication Auteurs : Keng-Hao Liu, Auteur ; Yen-Yu Lin, Auteur ; Chu-Song Chen, Auteur Année de publication : 2015 Article en page(s) : pp 2254 - 2269 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse linéaire des mélanges spectraux
[Termes IGN] apprentissage automatique
[Termes IGN] classification automatique
[Termes IGN] image hyperspectraleRésumé : (Auteur) Linear spectral mixture analysis (LSMA) has received wide interests for spectral unmixing in the remote sensing community. This paper introduces a framework called multiplekernel learning-based spectral mixture analysis (MKL-SMA) that integrates a newly proposed MKL method into the training process of LSMA. MKL-SMA allows us to adopt a set of nonlinear basis kernels to better characterize the data so that it can enrich the discriminant capability in classification. Because a single kernel is often insufficient to well present all the data characteristics, MKL-SMA has the advantage of providing a broader range of representation flexibilities; it also eases the kernel selection process because the kernel combination parameters can be learned automatically. Unlike most MKL approaches where complex nonlinear optimization problems are involved in their training process, we derived a closed-form solution of the kernel combination parameters in MKL-SMA. Our method is thus efficient for training and easy to implement. The usefulness of MKL-SMA is demonstrated by conducting real hyperspectral image experiments for performance evaluation. Promising results manifest the effectiveness of the proposed MKL-SMA. Numéro de notice : A2015-173 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2358620 Date de publication en ligne : 29/09/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2358620 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75891
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 4 (April 2015) . - pp 2254 - 2269[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015041 RAB Revue Centre de documentation En réserve L003 Disponible Fast subpixel mapping algorithms for subpixel resolution change detection / Qunming Wang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 4 (April 2015)
[article]
Titre : Fast subpixel mapping algorithms for subpixel resolution change detection Type de document : Article/Communication Auteurs : Qunming Wang, Auteur ; Peter M. Atkinson, Auteur ; Wenzhong Shi, Auteur Année de publication : 2015 Article en page(s) : pp 1692 - 1706 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification pixellaire
[Termes IGN] détection de changement
[Termes IGN] fonction de base radiale
[Termes IGN] image satellite
[Termes IGN] interpolation bicubique
[Termes IGN] interpolation bilinéaire
[Termes IGN] krigeage
[Termes IGN] précision infrapixellaireRésumé : (Auteur) Due to rapid changes on the Earth's surface, it is important to perform land cover change detection (CD) at a fine spatial and fine temporal resolution. However, remote sensing images with both fine spatial and temporal resolutions are commonly not available or, where available, may be expensive to obtain. This paper attempts to achieve fine spatial and temporal resolution land cover CD with a new computer technology based on subpixel mapping (SPM): The fine spatial resolution land cover maps (FRMs) are first predicted through SPM of the coarse spatial but fine temporal resolution images, and then, subpixel resolution CD is performed by comparison of class labels in the SPM results. For the first time, five fast SPM algorithms, including bilinear interpolation, bicubic interpolation, subpixel/pixel spatial attraction model, Kriging, and radial basis function interpolation methods, are proposed for subpixel resolution CD. The auxiliary information from the known FRM on one date is incorporated in SPM of coarse images on other dates to increase the CD accuracy. Based on the five fast SPM algorithms and the availability of the FRM, subpixels for each class are predicted by comparison of the estimated soft class values at the target fine spatial resolution and borrowing information from the FRM. Experiments demonstrate the feasibility of the five SPM algorithms using FRM in subpixel resolution CD. They are fast methods to achieve subpixel resolution CD. Numéro de notice : A2015-174 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2346535 Date de publication en ligne : 26/08/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2346535 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75892
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 4 (April 2015) . - pp 1692 - 1706[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015041 RAB Revue Centre de documentation En réserve L003 Disponible Classifying compound structures in satellite images : A compressed representation for fast queries / Lionel Gueguen in IEEE Transactions on geoscience and remote sensing, vol 53 n° 4 (April 2015)
[article]
Titre : Classifying compound structures in satellite images : A compressed representation for fast queries Type de document : Article/Communication Auteurs : Lionel Gueguen, Auteur Année de publication : 2015 Article en page(s) : pp 1803 - 1818 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification orientée objet
[Termes IGN] image multibande
[Termes IGN] image optique
[Termes IGN] occupation du sol
[Termes IGN] segmentation d'imageRésumé : (Auteur) With the increased spatial resolution of current sensor constellations, more details are captured about our changing planet, enabling the recognition of a greater range of land use/land cover classes. While pixeland object-based classification approaches are widely used for extracting information from imagery, recent studies have shown the importance of spatial contexts for discriminating more specific and challenging classes. This paper proposes a new compact representation for the fast query/classification of compound structures from very high resolution optical remote sensing imagery. This bag-of-features representation relies on the multiscale segmentation of the input image and the quantization of image structures pooled into visual word distributions for the characterization of compound structures. A compressed form of the visual word distributions is described, allowing adaptive and fast queries/classification of image patterns. The proposed representation and the query methodology are evaluated for the classification of the UC Merced 21-class data set, for the detection of informal settlements and for the discrimination of challenging agricultural classes. The results show that the proposed representation competes with state-of-the-art techniques. In addition, the complexity analysis demonstrates that the representation requires about 5% of the image storage space while allowing us to perform queries at a speed down to 1 s/ 1000 km2/CPU for 2-m multispectral data. Numéro de notice : A2015-175 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2348864 Date de publication en ligne : 04/09/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2348864 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75894
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 4 (April 2015) . - pp 1803 - 1818[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015041 RAB Revue Centre de documentation En réserve L003 Disponible Wuhan ionospheric oblique-incidence sounding system and its new application in localization of ionospheric irregularities / Shu-Zhu Shi in IEEE Transactions on geoscience and remote sensing, vol 53 n° 4 (April 2015)
[article]
Titre : Wuhan ionospheric oblique-incidence sounding system and its new application in localization of ionospheric irregularities Type de document : Article/Communication Auteurs : Shu-Zhu Shi, Auteur ; Gang Chen, Auteur ; Guo-Bin Yang, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 2185 - 2194 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] écho radar
[Termes IGN] forme d'onde
[Termes IGN] ionosphère
[Termes IGN] perturbation ionosphérique
[Termes IGN] positionnement différentiel
[Termes IGN] sonde spatialeRésumé : (Auteur) In this paper, a novel oblique-incidence ionosonde (Wuhan Ionospheric Oblique-Incidence Sounding System) and its new application in the localization of the ionospheric irregularities are presented. Due to the usage of the binary-phase-coded waveform, a large signal processing gain, a high Doppler and range resolution, and a large unambiguous detection range can be achieved in this ionosonde. This ionosonde also adopts the peripheral component interconnect extensions for instruments (PXI) bus technology and is designed as a small-sized PXI-based system. Furthermore, a high-performance oven-controlled crystal oscillator that is disciplined by the Global Positioning System is used to achieve a good time and frequency synchronization. With multichannel digital receiver and multiple receiving sites, this ionosonde can be applied in the localization of the ionospheric irregularities. The details of the system configuration, the ambiguity function of the sounding waveforms, the signal processing algorithm, and the time and frequency synchronization method are described. The experimental results show that the virtual height along with the ground position of the ionospheric field-aligned irregularities can be preliminarily localized with this ionosonde. Numéro de notice : A2015-176 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2357443 Date de publication en ligne : 26/09/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2357443 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75895
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 4 (April 2015) . - pp 2185 - 2194[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015041 RAB Revue Centre de documentation En réserve L003 Disponible CAESAR: an approach based on covariance matrix decomposition to improve multibaseline–multitemporal interferometric SAR processing / Gianfranco Fornaro in IEEE Transactions on geoscience and remote sensing, vol 53 n° 4 (April 2015)
[article]
Titre : CAESAR: an approach based on covariance matrix decomposition to improve multibaseline–multitemporal interferometric SAR processing Type de document : Article/Communication Auteurs : Gianfranco Fornaro, Auteur ; Simona Verde, Auteur ; Diego Reale, Auteur ; Antonio Pauciullo, Auteur Année de publication : 2015 Article en page(s) : pp 2050 - 2065 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse en composantes principales
[Termes IGN] décomposition d'image
[Termes IGN] image Cosmo-Skymed
[Termes IGN] image radar moirée
[Termes IGN] interferométrie différentielle
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] matrice de covariance
[Termes IGN] surveillance géologique
[Termes IGN] tomographie radarRésumé : (Auteur) Synthetic aperture radar (SAR) tomography has been strongly developed in the last years for the analysis at fine scale of data acquired by high-resolution interferometric SAR sensors as a technique alternative to classical persistent scatterer interferometry and able to resolve also multiple scatterers. SqueeSAR is a recently proposed solution which, in the context of SAR interferometry at the coarse scale analysis stage, allows taking advantage of the multilook operation to filter interferometric stacks by extracting, pixel by pixel, equivalent scattering mechanisms from the set of all available interferometric measurement collected in the data covariance matrix. In this paper, we investigate the possibilities to extend SqueeSAR by allowing the identification of multiple scattering mechanisms from the analysis of the covariance matrix. In particular, we present a new approach, named “Component extrAction and sElection SAR” algorithm, that allows taking advantage of the principal component analysis to filter interferograms relevant to the decorrelating scatterer, i.e., scatterers that may exhibit coherence losses depending on the spatial and temporal baseline distributions, and to detect and separate scattering mechanisms possibly interfering in the same pixel due to layover directly at the interferogram generation stage. The proposed module allows providing options useful for classical interferometric processing to monitor ground deformations at lower resolution (coarse scale), as well as for possibly aiding the data calibration preliminary for the subsequent full-resolution interferometric/tomographic (fine scale) analysis. Results achieved by processing high-resolution Cosmo-SkyMed data, characterized by the favorable features of a large baseline span, are presented to explain the advantages and validate this new interferometric processing solution. Numéro de notice : A2015-178 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2352853 Date de publication en ligne : 29/09/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2352853 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75897
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 4 (April 2015) . - pp 2050 - 2065[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015041 RAB Revue Centre de documentation En réserve L003 Disponible NL-SAR : a unified nonlocal framework for resolution-preserving (Pol) (In) SAR denoising / Charles-Alban Deledalle in IEEE Transactions on geoscience and remote sensing, vol 53 n° 4 (April 2015)
[article]
Titre : NL-SAR : a unified nonlocal framework for resolution-preserving (Pol) (In) SAR denoising Type de document : Article/Communication Auteurs : Charles-Alban Deledalle, Auteur ; Loïc Denis, Auteur ; Florence Tupin, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 2021 - 2038 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] filtrage du bruit
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] Pol-INSAR
[Termes IGN] polarimétrie radarRésumé : (Auteur) Speckle noise is an inherent problem in coherent imaging systems such as synthetic aperture radar. It creates strong intensity fluctuations and hampers the analysis of images and the estimation of local radiometric, polarimetric, or interferometric properties. Synthetic aperture radar (SAR) processing chains thus often include a multilooking (i.e., averaging) filter for speckle reduction, at the expense of a strong resolution loss. Preservation of point-like and fine structures and textures requires to adapt locally the estimation. Nonlocal (NL)-means successfully adapt smoothing by deriving data-driven weights from the similarity between small image patches. The generalization of nonlocal approaches offers a flexible framework for resolution-preserving speckle reduction. We describe a general method, i.e., NL-SAR, that builds extended nonlocal neighborhoods for denoising amplitude, polarimetric, and/or interferometric SAR images. These neighborhoods are defined on the basis of pixel similarity as evaluated by multichannel comparison of patches. Several nonlocal estimations are performed, and the best one is locally selected to form a single restored image with good preservation of radar structures and discontinuities. The proposed method is fully automatic and handles single and multilook images, with or without interferometric or polarimetric channels. Efficient speckle reduction with very good resolution preservation is demonstrated both on numerical experiments using simulated data, airborne, and spaceborne radar images. The source code of a parallel implementation of NL-SAR is released with this paper. Numéro de notice : A2015-177 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2352555 En ligne : https://doi.org/10.1109/TGRS.2014.2352555 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75905
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 4 (April 2015) . - pp 2021 - 2038[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015041 RAB Revue Centre de documentation En réserve L003 Disponible