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Non-invasive forest litter characterization using full-wave inversion of microwave radar data / Frédéric André in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 2 (February 2015) . - pp 828 - 840 Titre : Non-invasive forest litter characterization using full-wave inversion of microwave radar data Type de document : Article/Communication Auteurs : Frédéric André, Auteur ; Mathieu Jonard, Auteur ; Sébastien Lambot, Auteur Année de publication : 2015 Article en page(s) : pp 828 - 840 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] caractérisation [Termes IGN] déchet organique [Termes IGN] Fagus (genre) [Termes IGN] forêt [Termes IGN] forme d'onde pleine [Termes IGN] humidité du sol [Termes IGN] image radar [Termes IGN] litière [Termes IGN] radar pénétrant GPR [Termes IGN] rétrodiffusion [Termes IGN] sol forestier [Termes IGN] télédétection en hyperfréquence Résumé : (Auteur) Litter is acknowledged to affect microwave remote sensing data over forests, and accurate quantification of litter radiative properties is essential for proper retrieval of forest soil water content and forest canopy biophysical characteristics from satellite or airborne sensors. Furthermore, detailed characterization of forest soil organic horizons is of paramount importance for ecological studies and for carbon cycle and global changerelated studies. Ultrawideband ground-penetrating radar (GPR) data acquired above beech forest litter were used to analyze the effects of litter on the backscattering and investigate the ability of GPR to quantitatively characterize the properties of the forest floor. Radar measurements were performed over different litter configurations (i.e., single layers of recently fallen litter (OL) or of fragmented litter (OF), and combined OL-OF layers) and thicknesses. Radar data were processed through full-wave inversion. Over the considered frequency range (0.8-4.0 GHz), attenuation of the radar signal increased as both frequency and litter thickness increase, due to scattering and dielectric losses. These effects were accounted for in the radar model through frequency dependence of litter apparent electrical conductivity. Good agreement (RMSE = 9.5 × 10-3 m) was observed between estimated and measured litter thicknesses. Radar data inversions provided reliable estimates of litter electromagnetic properties, with relative dielectric permittivity values around 1.2 and 3.9 for OL and OF litters, respectively, and corresponding values of 0.032 and 0.080 Sm-1 for litter apparent electrical conductivity at 4.0 GHz. These results show great promise for the use of GPR for noninvasive characterization of forest litter. Numéro de notice : A2015-102 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2328776 En ligne : https://doi.org/10.1109/TGRS.2014.2328776 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75620 [article]

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Hyperspectral Band Selection by Multitask Sparsity Pursuit / Yuan Yuan in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 2 (February 2015) . - pp 631 -644 Titre : Hyperspectral Band Selection by Multitask Sparsity Pursuit Type de document : Article/Communication Auteurs : Yuan Yuan, Auteur ; Qi Wang, Auteur Année de publication : 2015 Article en page(s) : pp 631 -644 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage dirigé [Termes IGN] bande spectrale [Termes IGN] classification multibande [Termes IGN] couleur à l'écran [Termes IGN] image hyperspectrale [Termes IGN] visualisation de données Résumé : (Auteur) Hyperspectral images have been proved to be effective for a wide range of applications; however, the large volume and redundant information also bring a lot of inconvenience at the same time. To cope with this problem, hyperspectral band selection is a pertinent technique, which takes advantage of removing redundant components without compromising the original contents from the raw image cubes. Because of its usefulness, hyperspectral band selection has been successfully applied to many practical applications of hyperspectral remote sensing, such as land cover map generation and color visualization. This paper focuses on groupwise band selection and proposes a new framework, including the following contributions: 1) a smart yet intrinsic descriptor for efficient band representation; 2) an evolutionary strategy to handle the high computational burden associated with groupwise-selection-based methods; and 3) a novel MTSP-based criterion to evaluate the performance of each candidate band combination. To verify the superiority of the proposed framework, experiments have been conducted on both hyperspectral classification and color visualization. Experimental results on three real-world hyperspectral images demonstrate that the proposed framework can lead to a significant advancement in these two applications compared with other competitors. Numéro de notice : A2015-103 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2326655 En ligne : https://doi.org/10.1109/TGRS.2014.2326655 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75621 [article]

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Sparse unmixing of hyperspectral data using spectral a priori information / Wei Tang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 2 (February 2015) . - pp 770 - 783 Titre : Sparse unmixing of hyperspectral data using spectral a priori information Type de document : Article/Communication Auteurs : Wei Tang, Auteur ; Zhenwei Shi, Auteur ; Ying Wu, Auteur ; Changshui Zhang, Auteur Année de publication : 2015 Article en page(s) : pp 770 - 783 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse des mélanges spectraux [Termes IGN] classification spectrale [Termes IGN] image hyperspectrale Résumé : (Auteur) Given a spectral library, sparse unmixing aims at finding the optimal subset of endmembers from it to model each pixel in the hyperspectral scene. However, sparse unmixing still remains a challenging task due to the usually high mutual coherence of the spectral library. In this paper, we exploit the spectral a priori information in the hyperspectral image to alleviate this difficulty. It assumes that some materials in the spectral library are known to exist in the scene. Such information can be obtained via field investigation or hyperspectral data analysis. Then, we propose a novel model to incorporate the spectral a priori information into sparse unmixing. Based on the alternating direction method of multipliers, we present a new algorithm, which is termed sparse unmixing using spectral a priori information (SUnSPI), to solve the model. Experimental results on both synthetic and real data demonstrate that the spectral a priori information is beneficial to sparse unmixing and that SUnSPI can exploit this information effectively to improve the abundance estimation. Numéro de notice : A2015-104 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2328336 En ligne : https://doi.org/10.1109/TGRS.2014.2328336 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75622 [article]

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Stable mean-shift algorithm and its application to the segmentation of arbitrarily large remote sensing images / Julien Michel in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 2 (February 2015) . - pp 952 - 964 Titre : Stable mean-shift algorithm and its application to the segmentation of arbitrarily large remote sensing images Type de document : Article/Communication Auteurs : Julien Michel, Auteur ; David Youssefi, Auteur ; Manuel Grizonnet, Auteur Année de publication : 2015 Article en page(s) : pp 952 - 964 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] algorithme de décalage moyen [Termes IGN] dalle [Termes IGN] image à très haute résolution [Termes IGN] image satellite [Termes IGN] segmentation d'image [Termes IGN] stabilité [Termes IGN] télédétection spatiale Résumé : (Auteur) Segmentation of real-world remote sensing images is challenging because of the large size of those data, particularly for very high resolution imagery. However, a lot of high-level remote sensing methods rely on segmentation at some point and are therefore difficult to assess at full image scale, for real remote sensing applications. In this paper, we define a new property called stability of segmentation algorithms and demonstrate that piece- or tile-wise computation of a stable segmentation algorithm can be achieved with identical results with respect to processing the whole image at once. We also derive a technique to empirically estimate the stability of a given segmentation algorithm and apply it to four different algorithms. Among those algorithms, the mean-shift algorithm is found to be quite unstable. We propose a modified version of this algorithm enforcing its stability and thus allowing for tile-wise computation with identical results. Finally, we present results of this method and discuss the various trends and applications. Numéro de notice : A2015-105 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2330857 En ligne : https://doi.org/10.1109/TGRS.2014.2330857 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75623 [article]

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Gabor feature-based collaborative representation for hyperspectral imagery classification / Sen Jia in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 2 (February 2015) . - pp 1118 - 1129 Titre : Gabor feature-based collaborative representation for hyperspectral imagery classification Type de document : Article/Communication Auteurs : Sen Jia, Auteur ; Linlin Shen, Auteur ; Qingquan Li, Auteur Année de publication : 2015 Article en page(s) : pp 1118 - 1129 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification spectrale [Termes IGN] conception collaborative [Termes IGN] état de l'art [Termes IGN] extraction de traits caractéristiques [Termes IGN] filtre de Gabor [Termes IGN] image hyperspectrale [Termes IGN] précision de la classification Résumé : (Auteur) Sparse-representation-based classification (SRC) assigns a test sample to the class with minimum representation error via a sparse linear combination of all the training samples, which has successfully been applied to several pattern recognition problems. According to compressive sensing theory, the l1-norm minimization could yield the same sparse solution as the l0 norm under certain conditions. However, the computational complexity of the l1-norm optimization process is often too high for large-scale high-dimensional data, such as hyperspectral imagery (HSI). To make matter worse, a large number of training data are required to cover the whole sample space, which is difficult to obtain for hyperspectral data in practice. Recent advances have revealed that it is the collaborative representation but not the l1-norm sparsity that makes the SRC scheme powerful. Therefore, in this paper, a 3-D Gabor feature-based collaborative representation (3GCR) approach is proposed for HSI classification. When 3-D Gabor transformation could significantly increase the discrimination power of material features, a nonparametric and effective l2-norm collaborative representation method is developed to calculate the coefficients. Due to the simplicity of the method, the computational cost has been substantially reduced; thus, all the extracted Gabor features can be directly utilized to code the test sample, which conversely makes the l2-norm collaborative representation robust to noise and greatly improves the classification accuracy. The extensive experiments on two real hyperspectral data sets have shown higher performance of the proposed 3GCR over the state-of-the-art methods in the literature, in terms of both the classifier complexity and generalization ability from very small training sets. Numéro de notice : A2015-106 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2334608 En ligne : 10.1109/TGRS.2014.2334608 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75624 [article]

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Calibration of SAR polarimetric images by means of a covariance matching approach / Alberto Villa in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 2 (February 2015) . - pp 674 - 686 Titre : Calibration of SAR polarimetric images by means of a covariance matching approach Type de document : Article/Communication Auteurs : Alberto Villa, Auteur ; Lorenzo Iannini, Auteur ; Davide Giudici, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 674 - 686 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] appariement d'images [Termes IGN] covariance [Termes IGN] données polarimétriques [Termes IGN] étalonnage des données [Termes IGN] image ALOS-PALSAR [Termes IGN] image radar moirée [Termes IGN] matrice de covariance [Termes IGN] polarimétrie radar Résumé : (Auteur) In this paper, a numerical method optimizer based on covariance matching is proposed for synthetic aperture radar (SAR) polarimetric calibration. The method makes use of the information provided by a distributed target and a corner reflector in order to jointly estimate the system polarimetric distortion parameters and the Faraday rotation. A preliminary analysis is conducted to show the expected accuracy values and to identify the intrinsic ambiguities of the problem. Results from simulations are shown to assess the accuracy and convergence of the method. Finally, tests have been conducted on stack of repeated full polarimetric ALOS PALSAR images to check the stability of the retrieved distortion parameters in a realistic case. Numéro de notice : A2015-107 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2326955 En ligne : https://doi.org/10.1109/TGRS.2014.2326955 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75625 [article]

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Capabilities of BIOMASS tomography for investigating tropical forests / Ho Tong Minh Dinh in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 2 (February 2015) . - pp 965 - 975 Titre : Capabilities of BIOMASS tomography for investigating tropical forests Type de document : Article/Communication Auteurs : Ho Tong Minh Dinh, Auteur ; Stefano Tebaldini, Auteur ; Fabio Rocca, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 965 - 975 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] bande P [Termes IGN] Biomass [Termes IGN] biomasse (combustible) [Termes IGN] dégradation d'image [Termes IGN] forêt équatoriale [Termes IGN] Guyane française [Termes IGN] hauteur des arbres [Termes IGN] image aérienne [Termes IGN] image radar moirée [Termes IGN] tomographie radar Résumé : (Auteur) The objective of this paper is to provide a better understanding of the capabilities of the BIOMASS tomography concerning the retrieval of forest biomass and height in tropical areas. The analysis presented in this paper is carried out on airborne data acquired by Office National d'Etudes et de Recherches Aérospatiales (ONERA) over the site of Paracou, French Guiana, during the European Space Agency campaign TropiSAR. This high-resolution data set (125-MHz bandwidth) was reprocessed in order to generate a new data stack consistent with BIOMASS as for the bandwidth (6 MHz) and the azimuth resolution (about 12 m). To do this, two different processing approaches have been considered. One approach consisted of degrading the resolution of the airborne data through the linear filtering of raw data, followed by standard SAR processing. The other approach consisted of recovering the 3-D distribution of the scatterers at a high resolution, which was then reprojected onto the BIOMASS geometry. The latter procedure allows us to obtain a data stack that is the most realistic emulation of BIOMASS imaging capabilities. In both approaches, neither ionospheric disturbances nor temporal decorrelation has been considered. The connection to the forest biomass has been examined in both cases by investigating the correlation between the backscatter at different forest heights and the above-ground biomass (AGB) values from in situ data. As expected, the reduction of the system bandwidth to 6 MHz resulted in significant vertical resolution losses compared with the original airborne data. Nevertheless, it was possible to retrieve the forest height to within an accuracy of better than 4 m, whereas the backscattered power at the volume height (30 m above the ground) exhibited a correlation higher than 0.8 with the in situ data and no bias phenomena over the AGB values ranging from 250 to 450 t/ha. Numéro de notice : A2015-108 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2331142 En ligne : https://doi.org/10.1109/TGRS.2014.2331142 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75626 [article]

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Temporal decorrelation in L-, C-, and X-band satellite radar interferometry for pasture on drained cs / Yu Morishita in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 2 (February 2015) . - pp 1096 - 1104 Titre : Temporal decorrelation in L-, C-, and X-band satellite radar interferometry for pasture on drained cs Type de document : Article/Communication Auteurs : Yu Morishita, Auteur ; Ramon F. Hanssen, Auteur Année de publication : 2015 Article en page(s) : pp 1096 - 1104 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] bande C [Termes IGN] bande L [Termes IGN] bande X [Termes IGN] décorrélation [Termes IGN] humidité du sol [Termes IGN] image ALOS [Termes IGN] image Sentinel-SAR [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] paturage [Termes IGN] tourbe [Termes IGN] traitement d'image radar [Termes IGN] zone rurale Résumé : (Auteur) Temporal decorrelation is one of the main limitations of synthetic aperture radar (SAR) interferometry. For nonurban areas, its mechanism is very complex, as it is very dependent of vegetation types and their temporal dynamics, actual land use, soil types, and climatological circumstances. Yet, an a priori assessment and comprehension of the expected coherence levels of interferograms are required for designing new satellite missions (in terms of frequency, resolution, and repeat orbits), for choosing the optimal data sets for a specific application, and for feasibility studies for new interferometric applications. Although generic models for temporal decorrelation have been proposed, their parameters depend heavily on the land use in the area of interest. Here, we report the behavior of temporal decorrelation for a specific class of land use: pasture on drained peat soils. We use L-, C-, and X-band SAR observations from the Advanced Land Observation Satellite (ALOS), European Remote Sensing Satellite, Envisat, RADARSAT-2, and TerraSAR-X missions. We present a dedicated temporal decorrelation model using three parameters and demonstrate how coherent information can be retrieved as a function of frequency, repeat intervals, and coherence estimation window sizes. New satellites such as Sentinel-1 and ALOS-2, with shorter repeat intervals than their predecessors, would enhance the possibility to obtain a coherent signal over pasture. Numéro de notice : A2015-109 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2333814 En ligne : https://doi.org/10.1109/TGRS.2014.2333814 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75627 [article]

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Geometry-information-aided efficient radial velocity estimation for moving target imaging and location based on Radon transform / Xuepan Zhang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 2 (February 2015) . - pp 1105 - 1117 Titre : Geometry-information-aided efficient radial velocity estimation for moving target imaging and location based on Radon transform Type de document : Article/Communication Auteurs : Xuepan Zhang, Auteur ; Guisheng Liao, Auteur ; Shengqi Zhu, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 1105 - 1117 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] géométrie [Termes IGN] image radar moirée [Termes IGN] objet mobile [Termes IGN] transformation de Radon [Termes IGN] vitesse radiale Résumé : (Auteur) Real-time radial velocity estimation is a key challenge for moving target imaging and location in current single-antenna synthetic aperture radar (SAR)-ground moving target indication systems. Since the conventional methods suffer from ambiguity, complexity realization, or heavy computation load for fast moving target motion estimation, this paper emphasizes the estimation efficiency by simple realization. An efficient Radon transform (RT) estimation is proposed to estimate the radial velocity of fast moving target by utilizing the geometry information, and much more geometry information is exploited to realize clutter cancellation, noise cancellation, and estimation error minimizing in the RT domain, which is not proposed by the others. With only two to four angles used to calculate rather than search for the radial velocity of moving targets, the proposed methods simplify the conventional range and angle (2-D) searching procedure into several time range (1-D) searching procedure efficiently. The theoretical and experimental analysis provides qualitative and quantitative evaluations into the effectiveness of the proposed methods. In the single-antenna SAR system, the proposed methods can estimate the radial velocity of fast moving target efficiently and accurately in high signal to clutter plus noise ratio scenarios. Numéro de notice : A2015-110 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2334322 En ligne : https://doi.org/10.1109/TGRS.2014.2334322 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75628 [article]

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LiDAR strip adjustment using multifeatures matched with aerial images / Yongjun Zhang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 2 (February 2015) . - pp 976 - 987 Titre : LiDAR strip adjustment using multifeatures matched with aerial images Type de document : Article/Communication Auteurs : Yongjun Zhang, Auteur ; Xiaodong Xiong, Auteur ; Maoteng Zheng, Auteur ; Xu Huang, Auteur Année de publication : 2015 Article en page(s) : pp 976 - 987 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] aérotriangulation numérique [Termes IGN] angle de visée [Termes IGN] compensation par bloc [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] erreur systématique [Termes IGN] image aérienne [Termes IGN] ligne de visée [Termes IGN] positionnement automatique [Termes IGN] semis de points Résumé : (Auteur) Airborne light detecting and ranging (LiDAR) systems have been widely used for the fast acquisition of dense topographic data. Regrettably, coordinate errors always exist in LiDAR-acquired points. The errors are attributable to several sources, such as laser ranging errors, sensor mounting errors, and position and orientation system (POS) systematic errors, among others. LiDAR strip adjustment (LSA) is the solution to eliminating the errors, but most state-of-the-art LSA methods neglect the influence from POS systematic errors by assuming that the POS is precise enough. Unfortunately, many of the LiDAR systems used in China are equipped with a low-precision POS due to cost considerations. Subsequently, POS systematic errors should be also considered in the LSA. This paper presents an aerotriangulation-aided LSA (AT-aided LSA) method whose major task is eliminating position and angular errors of the laser scanner caused by boresight angular errors and POS systematic errors. The aerial images, which cover the same area with LiDAR strips, are aerotriangulated and serve as the reference data for LSA. Two types of conjugate features are adopted as control elements (i.e., the conjugate points matched between the LiDAR intensity images and the aerial images and the conjugate corner features matched between LiDAR point clouds and aerial images). Experiments using the AT-aided LSA method are conducted using a real data set, and a comparison with the three-dimensional similarity transformation (TDST) LSA method is also performed. Experimental results support the feasibility of the proposed AT-aided LSA method and its superiority over the TDST LSA method. Numéro de notice : A2015-111 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2331234 En ligne : https://doi.org/10.1109/TGRS.2014.2331234 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75629 [article]

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