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[n° ou bulletin]
est un bulletin de IEEE Transactions on geoscience and remote sensing / IEEE Geoscience and remote sensing society (Etats-Unis) (1986 -) ![]()
[n° ou bulletin]
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Exemplaires(1)
Code-barres | Cote | Support | Localisation | Section | Disponibilité |
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065-2014091A | RAB | Revue | Centre de documentation | En réserve L003 | Disponible |
Dépouillements
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A 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)
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[article]
Titre : A novel rapid SAR simulator based on equivalent scatterers for three-dimensional forest canopies Type de document : Article/Communication Auteurs : Tao Zeng, Auteur ; Cheng Hu, Auteur ; Hanwei Sun, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 5243 - 5255 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] canopée
[Termes IGN] image radar
[Termes IGN] modèle de diffusion du rayonnement
[Termes IGN] rétrodiffusion
[Termes IGN] simulation 3D
[Termes IGN] traitement du signalRésumé : (Auteur) Synthetic aperture radar (SAR) simulation of 3-D forest canopies is a powerful tool for studying the interaction between radar and forest, for testing new applications, and for devising inversion algorithms of forest structures. SAR raw-signal generation is frequently used in point-target simulation but is rarely used in 3-D forest simulation. The existing simulators directly produce SAR images based on an impulse response function (IRF) without involving raw-signal generation and various nonideal factors. In this paper, a novel simulator to produce SAR images of 3-D forest canopies is proposed. It incorporates a SAR raw-signal generation process taking account of various nonideal factors such as trajectory deviation of radar platforms and complexity of natural environments, which is more faithful to realistic remote sensing systems. Furthermore, an approach to speed up the raw-signal generation is put forward based on the equivalent scattering model consisting of a few virtual scatterers with specially calculated positions and backscattering matrices. Thus, the raw signals received from the entire forest canopy can be equivalent to those from virtual scatterers in the case of tiny slant-range errors. The error sensitivity of equivalent conditions is analyzed, and the optimum selection of equivalent parameters is derived considering the compromise between precision and efficiency. The results of simulation and forest height inversion demonstrate the feasibility and potential utilities of the proposed simulator. Numéro de notice : A2014-438 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2287691 En ligne : https://doi.org/10.1109/TGRS.2013.2287691 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73975
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 9 Tome 1 (September 2014) . - pp 5243 - 5255[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2014091A RAB Revue Centre de documentation En réserve L003 Disponible Land cover and soil type mapping from spaceborne PolSAR Data at L-Band with probabilistic neural network / Oleg Antropov in IEEE Transactions on geoscience and remote sensing, vol 52 n° 9 Tome 1 (September 2014)
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[article]
Titre : Land cover and soil type mapping from spaceborne PolSAR Data at L-Band with probabilistic neural network Type de document : Article/Communication Auteurs : Oleg Antropov, Auteur ; Yrjö Rauste, Auteur ; Heikki Astola, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 5256 - 5270 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] classification dirigée
[Termes IGN] données polarimétriques
[Termes IGN] forêt boréale
[Termes IGN] image ALOS-PALSAR
[Termes IGN] réseau neuronal artificiel
[Termes IGN] solRésumé : (Auteur) This paper evaluates performance of fully polarimetric SAR (PolSAR) data in several land cover mapping studies in the boreal forest environment, taking advantage of the high canopy penetration capability at L-band. The studies included multiclass land cover mapping, forest-nonforest delineation, and classification of soil type under vegetation. PolSAR data used in the study were collected by the ALOS PALSAR sensor in 2006-2007 over a managed boreal forest site in Finland. A supervised classification approach using selected polarimetric features in the framework of probabilistic neural network (PNN) was adopted in the study. It has no assumptions about statistics of the polarimetric features, using nonparametric estimation of probability distribution functions instead. The PNN-based method improved classification accuracy compared with standard maximum-likelihood approach. The improvement was considerably strong for soil type mapping under vegetation, indicating notable non-Gaussian effects in the PolSAR data even at L-band. The classification performance was strongly dependent on seasonal conditions. The PolSAR feature data set was further modified to include a number of recently proposed polarimetric parameters (surface scattering fraction and scattering diversity), reducing the computational complexity at practically no loss in the classification accuracy. The best obtained accuracies of up to 82.6% in five-class land cover mapping and more than 90% in forest-nonforest mapping in wall-to-wall validation indicate suitability of PolSAR data for wide-area land cover and forest mapping. Numéro de notice : A2014-439 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2287712 En ligne : https://doi.org/10.1109/TGRS.2013.2287712 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73976
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 9 Tome 1 (September 2014) . - pp 5256 - 5270[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2014091A RAB Revue Centre de documentation En réserve L003 Disponible Hybrid geometric optical–radiative transfer model suitable for forests on slopes / Weiliang Fan in IEEE Transactions on geoscience and remote sensing, vol 52 n° 9 Tome 1 (September 2014)
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[article]
Titre : Hybrid geometric optical–radiative transfer model suitable for forests on slopes Type de document : Article/Communication Auteurs : Weiliang Fan, Auteur ; Jing M. Chen, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 5579 - 5586 Note générale : Bibliographie Langues : Anglais (eng) Résumé : (Auteur) A new geometric optical (GO)-radiative transfer (RT) model with a multiple scattering scheme suitable for sloping forest canopies is developed in this study. It is based on a Geometrical-Optical model for Sloping Terrains and an RT method. This new model overcomes the difficulty to prescribe bidirectional reflectance factors (BRFs) of shaded components (shaded foliage and background) in GO modeling through simulating radiation multiple scattering within a sloping forest. A case study shows that multiply scattered radiation depends on topographic factors and leaf area index. The contributions of the shaded components to stand-level BRF are less than 3% in the red band and can reach up to 40% in the near-infrared (NIR) band. The “multiangle” Moderate Resolution Imaging Spectroradiometer (MODIS) data over sloping pixels are selected to validate the modeled forest BRF. Considering the multiple scattering schemes and topographic factors, the modeled BRF is closer to the MODIS surface reflectance (BRF product) (red band: R2 = 0.8614, rRMSE = 0.1339; NIR band: R2 = 0.7573, rRMSE = 0.0850) than the modeled BRF (red band: R2 = 0.7771, rRMSE=0.1839; NIR band: R2 =0.5176, rRMSE = 0.1155) without topographic consideration. It is also shown that the MODIS surface reflectance of sloping forests at multiple angles can be simulated well using the newly developed model. Numéro de notice : A2014-441 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2290590 En ligne : https://doi.org/10.1109/TGRS.2013.2290590 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73978
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 9 Tome 1 (September 2014) . - pp 5579 - 5586[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2014091A RAB Revue Centre de documentation En réserve L003 Disponible Regularized simultaneous forward–backward greedy algorithm for sparse unmixing of hyperspectral data / Wei Tang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 9 Tome 1 (September 2014)
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[article]
Titre : Regularized simultaneous forward–backward greedy algorithm for sparse unmixing of hyperspectral data Type de document : Article/Communication Auteurs : Wei Tang, Auteur ; Zhenwei Shi, Auteur ; Y. Wu, Auteur Année de publication : 2014 Article en page(s) : pp 5271 - 5288 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] optimisation (mathématiques)Résumé : (Auteur) Sparse unmixing assumes that each observed signature of a hyperspectral image is a linear combination of only a few spectra (endmembers) in an available spectral library. It then estimates the fractional abundances of these endmembers in the scene. The sparse unmixing problem still remains a great difficulty due to the usually high correlation of the spectral library. Under such circumstances, this paper presents a novel algorithm termed as the regularized simultaneous forward-backward greedy algorithm (RSFoBa) for sparse unmixing of hyperspectral data. The RSFoBa has low computational complexity of getting an approximate solution for the l0 problem directly and can exploit the joint sparsity among all the pixels in the hyperspectral data. In addition, the combination of the forward greedy step and the backward greedy step makes the RSFoBa more stable and less likely to be trapped into the local optimum than the conventional greedy algorithms. Furthermore, when updating the solution in each iteration, a regularizer that enforces the spatial-contextual coherence within the hyperspectral image is considered to make the algorithm more effective. We also show that the sublibrary obtained by the RSFoBa can serve as input for any other sparse unmixing algorithms to make them more accurate and time efficient. Experimental results on both synthetic and real data demonstrate the effectiveness of the proposed algorithm. Numéro de notice : A2014-442 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2287795 En ligne : https://doi.org/10.1109/TGRS.2013.2287795 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73979
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 9 Tome 1 (September 2014) . - pp 5271 - 5288[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2014091A RAB Revue Centre de documentation En réserve L003 Disponible Shadow detection of man-made buildings in high-resolution panchromatic satellite images / Mohamed I. Elbakary in IEEE Transactions on geoscience and remote sensing, vol 52 n° 9 Tome 1 (September 2014)
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Titre : Shadow detection of man-made buildings in high-resolution panchromatic satellite images Type de document : Article/Communication Auteurs : Mohamed I. Elbakary, Auteur ; Khan M. Iftekharuddin, Auteur Année de publication : 2014 Article en page(s) : pp 5374 - 5386 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] détection automatique
[Termes IGN] détection d'ombre
[Termes IGN] détection de contours
[Termes IGN] détection du bâti
[Termes IGN] image à haute résolution
[Termes IGN] image panchromatique
[Termes IGN] segmentation d'imageRésumé : (Auteur) High-resolution satellite imagery is considered an excellent candidate for extracting information about the human activities on Earth. The information about residential development and suburban area mapping is of interest that can be obtained from these images. Shadow of structures such as man-made buildings is one of the main cues for structure detection in panchromatic high-resolution satellite imagery. However, to correctly exploit the information of the shadow in an image, the shadow needs to be detected and isolated first. In this paper, we propose a new algorithm for shadow detection and isolation of buildings in high-resolution panchromatic satellite imagery. The proposed algorithm is based on tailoring the traditional model of the geometric active contours such that the new model of the contours is systematically biased toward segmenting the shadow and the dark regions in the image. The systematic biasing in the proposed contour model is accomplished by novel encoding of the radiometric characteristics of the shadows regions. After detecting and segmenting the shadow and the dark regions in the image, further processing steps are introduced. The proposed postprocessing is based on selection of optimal threshold and a boundary complexity metric to distinguish the true shadows from the clutter. Experimental results are presented to validate the performance of the proposed algorithm on real high-resolution panchromatic satellite images. Numéro de notice : A2014-443 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2288500 En ligne : https://doi.org/10.1109/TGRS.2013.2288500 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73980
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 9 Tome 1 (September 2014) . - pp 5374 - 5386[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2014091A RAB Revue Centre de documentation En réserve L003 Disponible Image matching using SIFT features and relaxation labeling technique—A constraint initializing method for dense stereo matching / Jyoti Joglekar in IEEE Transactions on geoscience and remote sensing, vol 52 n° 9 Tome 1 (September 2014)
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[article]
Titre : Image matching using SIFT features and relaxation labeling technique—A constraint initializing method for dense stereo matching Type de document : Article/Communication Auteurs : Jyoti Joglekar, Auteur ; Shirish S. Gedam, Auteur ; B.K. Mohan, Auteur Année de publication : 2014 Article en page(s) : pp 5643 - 5652 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement d'images
[Termes IGN] appariement dense
[Termes IGN] processus stochastique
[Termes IGN] SIFT (algorithme)
[Termes IGN] vision stéréoscopiqueRésumé : (Auteur) A probabilistic neural-network-based feature-matching algorithm for a stereo image pair is presented in this paper, which will be useful as a constraint initializing method for further dense matching technique. In this approach, scale-invariant feature transform (SIFT) features are used to detect interest points in a stereo image pair. The descriptor which is associated with each keypoint is based on the histogram of the gradient magnitude and direction of gradients. These descriptors are the preliminary input for the matching algorithm. Using disparity range computed by visual inspection, the search area can be restricted for a given stereo image pair. Reduced search area improves the computation speed. Initial probabilities of matches are assigned to the keypoints which are considered as probable matches from the selected search area by Bayesian reasoning. The probabilities of all such matches are improved iteratively using relaxation labeling technique. Neighboring probable matches are exploited to improve the probability of best match using consistency measures. Confidence measures considering the neighborhood, unicity, and symmetry are some validation techniques which are built into the technique presented here for finding accurate matches. The algorithm is found to be effective in matching SIFT features detected in a stereo image pair with greater accuracy, and these accurate correspondences can be used in finding the fundamental matrix which encodes the epipolar geometry between the given stereo image pair. This fundamental matrix can then be used as a constraint for finding inliers that are used in matching methods for deriving dense disparity map. Numéro de notice : A2014-444 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2291685 En ligne : https://doi.org/10.1109/TGRS.2013.2291685 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73981
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 9 Tome 1 (September 2014) . - pp 5643 - 5652[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2014091A RAB Revue Centre de documentation En réserve L003 Disponible