IEEE Transactions on geoscience and remote sensing / IEEE Geoscience and remote sensing society (Etats-Unis) . vol 51 n° 12Paru le : 01/12/2013 ISBN/ISSN/EAN : 0196-2892 |
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Ajouter le résultat dans votre panierProcessing and calibration of submillimeter Fourier transform radiometer spectra from the RHUBC-II campaign / Scott N. Paine in IEEE Transactions on geoscience and remote sensing, vol 51 n° 12 (December 2013)
[article]
Titre : Processing and calibration of submillimeter Fourier transform radiometer spectra from the RHUBC-II campaign Type de document : Article/Communication Auteurs : Scott N. Paine, Auteur ; David D. Turner, Auteur Année de publication : 2013 Article en page(s) : pp 5187 - 5198 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] analyse en composantes principales
[Termes IGN] Chili
[Termes IGN] étalonnage radiométrique
[Termes IGN] précision submillimétrique
[Termes IGN] propagation troposphérique
[Termes IGN] radiosondage
[Termes IGN] spectromètre
[Termes IGN] transformation de FourierRésumé : (Auteur) The Radiative Heating in Underexplored Bands Campaign-II, conducted in 2009 from a high-altitude site in northern Chile, combined ground-based radiometry with radiosonde measurements of atmospheric state, for the purpose of testing atmospheric radiation models under conditions strongly influenced by water vapor in the middle to upper troposphere. A suite of broadband Fourier transform spectrometers (FTSs) measured the entire terrestrial thermal radiance spectrum from 1000- to 3.3-um wavelength. The submillimeter portion of the spectrum, from 1000 to 85 um (300-3500 GHz) was covered by a polarizing FTS referred to as the Smithsonian Astrophysical Observatory (SAO) FTS. Here, we describe data processing and radiometric calibration algorithms for this instrument. These include correction of interferograms for periodic sampled lag error, development of a temperature-dependent instrument calibration model, and principal component analysis of the complete set of spectra acquired during the campaign. Numéro de notice : A2013-693 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2231869 En ligne : https://doi.org/10.1109/TGRS.2012.2231869 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32829
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 12 (December 2013) . - pp 5187 - 5198[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013121 RAB Revue Centre de documentation En réserve L003 Disponible An entropy-based multispectral image classification algorithm / Di Long in IEEE Transactions on geoscience and remote sensing, vol 51 n° 12 (December 2013)
[article]
Titre : An entropy-based multispectral image classification algorithm Type de document : Article/Communication Auteurs : Di Long, Auteur ; Vijay P. Singh, Auteur Année de publication : 2013 Article en page(s) : pp 5225 - 5238 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] carte d'occupation du sol
[Termes IGN] classificateur
[Termes IGN] entropie maximale
[Termes IGN] Houston (Texas)
[Termes IGN] image Landsat-ETM+Résumé : (Auteur) Employing the entropy theory, this paper presents a new and robust multispectral image classification algorithm. The digital number (DN) in remotely sensed multispectral images is considered as a random variable when judging the allocation of unknown pixels into predefined training classes. If an unknown pixel shows a similar DN vector as the pixels in a training class, it will increase the global entropy defined as the sum of DN probabilities multiplied by the logarithm of DN probabilities for all pixels within the training class. The unknown pixel is to be assigned to the class for which the entropy of the training class is increased most due to the inclusion of the pixel. The proposed entropy-based classification (EC) is compared with the maximum likelihood classification (MLC), parallelepiped classification, minimum distance classification, Mahalanobis distance classification (MDC), iterative self-organizing data analysis technique (ISODATA) classification, and K-means classification. These classifiers were applied to a Landsat Enhanced Thematic Mapper Plus image covering Houston, Texas, USA, acquired on October 16, 1999. A reference land cover map from the National Land Cover Data 2001 of the same area was taken as a ground reference to assess the accuracy of classification results, suggesting that the EC showed comparable overall accuracy as MDC, and they both outperformed other classifiers. The results of MLC can be improved by substituting the multivariate lognormal or gamma distribution for the multivariate normal distribution involved in its assumption. The EC algorithm has the potential to produce reliable land cover maps regardless of the distribution of DN vectors and relevant parameters of probability density functions involved in other classifiers. Numéro de notice : A2013-694 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2272560 En ligne : https://doi.org/10.1109/TGRS.2013.2272560 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32830
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 12 (December 2013) . - pp 5225 - 5238[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013121 RAB Revue Centre de documentation En réserve L003 Disponible Orthorectification of full-polarimetric radarsat-2 data using accurate LIDAR DSM / Thierry Toutin in IEEE Transactions on geoscience and remote sensing, vol 51 n° 12 (December 2013)
[article]
Titre : Orthorectification of full-polarimetric radarsat-2 data using accurate LIDAR DSM Type de document : Article/Communication Auteurs : Thierry Toutin , Auteur ; Huili Wang, Auteur ; Pierre Chomaz, Auteur ; Eric Pottier, Auteur Année de publication : 2013 Article en page(s) : pp 5252 - 5258 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] correction géométrique
[Termes IGN] données de terrain
[Termes IGN] données lidar
[Termes IGN] données polarimétriques
[Termes IGN] image radar moirée
[Termes IGN] image Radarsat
[Termes IGN] modèle numérique de surface
[Termes IGN] orthorectification automatique
[Termes IGN] polarimétrie radarRésumé : (Auteur) Orthorectification using digital terrain models is a key issue for full-polarimetric complex SAR data because resampling the complex data can corrupt the polarimetric phase, mainly in terrain with relief. This research thus compared two methods for the orthorectification of the complex SAR data: The polarimetric processing is performed before (image-space method) or after (ground-space method) the geometric processing. Radarsat-2 fine-quad data acquired with different look angles over a hilly relief study site were orthorectified using accurate light detection and ranging digital surface model. Quantitative evaluations between the two methods as a function of different geometric and radiometric parameters were thus performed to evaluate the impact during orthorectification. The results demonstrated that the look angles and the terrain slopes can potentially corrupt the polarimetric complex SAR data during its orthorectification with the ground-space method. In addition, general advice is provided to reduce these impacts to an acceptable level for the users and their polarimetric applications. Numéro de notice : A2013-695 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2233206 En ligne : https://doi.org/10.1109/TGRS.2012.2233206 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32831
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 12 (December 2013) . - pp 5252 - 5258[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013121 RAB Revue Centre de documentation En réserve L003 Disponible Wavelet-Based Compressed Sensing for SAR Tomography of Forested Areas / Esteban Aguilera in IEEE Transactions on geoscience and remote sensing, vol 51 n° 12 (December 2013)
[article]
Titre : Wavelet-Based Compressed Sensing for SAR Tomography of Forested Areas Type de document : Article/Communication Auteurs : Esteban Aguilera, Auteur ; Matteo Nannini, Auteur ; Andreas Reigber, Auteur Année de publication : 2013 Article en page(s) : pp 5283 - 5295 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] Allemagne
[Termes IGN] bande L
[Termes IGN] compression par ondelettes
[Termes IGN] données polarimétriques
[Termes IGN] forêt
[Termes IGN] image E-SAR
[Termes IGN] image radar moirée
[Termes IGN] image Radarsat
[Termes IGN] polarimétrie radar
[Termes IGN] tomographie radarRésumé : (Auteur) Synthetic aperture radar (SAR) tomography is a 3-D imaging modality that is commonly tackled by spectral estimation techniques. Thus, the backscattered power along the cross-range direction can be readily obtained by computing the Fourier spectrum of a stack of multibaseline measurements. In addition, recent work has addressed the tomographic inversion under the framework of compressed sensing, thereby recovering sparse cross-range profiles from a reduced set of measurements. This paper differs from previous publications, in that it focuses on sparse expansions in the wavelet domain while working with the second-order statistics of the corresponding multibaseline measurements. In this regard, we elaborate on the conditions under which this perspective is applicable to forested areas and discuss the possibility of optimizing the acquisition geometry. Finally, we compare this approach with traditional nonparametric ones and validate it by using fully polarimetric L-band data acquired by the Experimental SAR (E-SAR) sensor of the German Aerospace Center (DLR). Numéro de notice : A2013-696 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2231081 En ligne : https://doi.org/10.1109/TGRS.2012.2231081 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32832
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 12 (December 2013) . - pp 5283 - 5295[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013121 RAB Revue Centre de documentation En réserve L003 Disponible SAR image categorization with log cumulants of the fractional Fourier transform coefficients / Jagmal Singh in IEEE Transactions on geoscience and remote sensing, vol 51 n° 12 (December 2013)
[article]
Titre : SAR image categorization with log cumulants of the fractional Fourier transform coefficients Type de document : Article/Communication Auteurs : Jagmal Singh, Auteur ; Mihai Dactu, Auteur Année de publication : 2013 Article en page(s) : pp 5273 - 5282 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] fractionnement
[Termes IGN] image radar moirée
[Termes IGN] image TanDEM-X
[Termes IGN] image TerraSAR-X
[Termes IGN] transformation de FourierRésumé : (Auteur) With the advent of high-resolution (HR) synthetic aperture radar (SAR) images from satellites like TerraSAR-X and TanDEM-X, interest is now on patch-oriented image categorization in contrast to the pixel-based classification in low-resolution SAR images. SAR image categorization requires the generation of a compact feature descriptor that accurately defines the content of the image patch under consideration. As phase information plays a critical role in SAR images, this paper proposes the use of a chirplet-derived transform, i.e., the fractional Fourier transform (FrFT), for generating a compact feature descriptor for single-look complex (SLC) SAR images. Representing a SAR signal in rotated joint time-frequency planes via the FrFT allows discovering the underlying backscattering phenomenon of the objects on the ground. SAR image projections on different planes of the joint time-frequency space using the FrFT provide a simple statistical response that is easier to analyze. The proposed method has been compared with a multiscale approach, i.e., Gabor filter banks, a second-order-statistics-based method (as gray-level co-occurrence matrices), and a spectral descriptor method. We demonstrate the suitability of the FrFT-based method for image categorization on the basis of backscattering behavior, whereas the Gabor-filter-bank-based method is found mainly suitable for images with a strong texture. This paper demonstrates enhancement in the separability for most of the considered categories when using logarithmic cumulants instead of linear moments for both the FrFT-based and Gabor-filter-bank-based methods. The experimental database consists of 2000 image patches (of size 200 200 pixels) extracted from SLC HR TerraSAR-X scenes. Numéro de notice : A2013-697 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2230892 En ligne : https://doi.org/10.1109/TGRS.2012.2230892 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32833
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 12 (December 2013) . - pp 5273 - 5282[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013121 RAB Revue Centre de documentation En réserve L003 Disponible