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Introducing spatial regularization in SAR tomography reconstruction / Clément Rambour in IEEE Transactions on geoscience and remote sensing, vol 57 n° 11 (November 2019)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 57 n° 11 (November 2019) . - pp 8600 - 8617 Titre : Introducing spatial regularization in SAR tomography reconstruction Type de document : Article/Communication Auteurs : Clément Rambour, Auteur ; Loïc Denis, Auteur ; Florence Tupin, Auteur ; Hélène Oriot, Auteur Année de publication : 2019 Article en page(s) : pp 8600 - 8617 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] acquisition comprimée [Termes descripteurs IGN] analyse spectrale [Termes descripteurs IGN] écho radar [Termes descripteurs IGN] fractionnement [Termes descripteurs IGN] image à très haute résolution [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] image TerraSAR-X [Termes descripteurs IGN] mécanique de Lagrange [Termes descripteurs IGN] reconstruction 3D du bâti [Termes descripteurs IGN] scène urbaine [Termes descripteurs IGN] TerraSAR-X [Termes descripteurs IGN] tomographie radar Résumé : (auteur) The resolution achieved by current synthetic aperture radar (SAR) sensors provides a detailed visualization of urban areas. Spaceborne sensors such as TerraSAR-X can be used to analyze large areas at a very high resolution. In addition, repeated passes of the satellite give access to temporal and interferometric information on the scene. Because of the complex 3-D structure of urban surfaces, scatterers located at different heights (ground, building facade, and roof) produce radar echoes that often get mixed within the same radar cells. These echoes must be numerically unmixed in order to get a fine understanding of the radar images. This unmixing is at the core of SAR tomography. SAR tomography reconstruction is generally performed in two steps: 1) reconstruction of the so-called tomogram by vertical focusing, at each radar resolution cell, to extract the complex amplitudes (a 1-D processing) and 2) transformation from radar geometry to ground geometry and extraction of significant scatterers. We propose to perform the tomographic inversion directly in ground geometry in order to enforce spatial regularity in 3-D space. This inversion requires solving a large-scale nonconvex optimization problem. We describe an iterative method based on variable splitting and the augmented Lagrangian technique. Spatial regularizations can easily be included in this generic scheme. We illustrate, on simulated data and a TerraSAR-X tomographic data set, the potential of this approach to produce 3-D reconstructions of urban surfaces. Numéro de notice : A2019-596 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2921756 date de publication en ligne : 04/07/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2921756 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94588 [article]

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)

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 4 (April 2015) . - pp 2021 - 2038 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 descripteurs IGN] filtrage du bruit [Termes descripteurs IGN] interféromètrie par radar à antenne synthétique [Termes descripteurs IGN] Pol-INSAR [Termes descripteurs IGN] polarimétrie radar Résumé : (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 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75905 [article]

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