3D imaging for underfoliage targets using L-band multibaseline polinsar data and sparse estimation methods

Abstract : SAR imaging of concealed targets beneath the canopies has to face a complex mixture of diverse scattering mechanisms. To characterize this complex scattering environment, nonpara-metric tomographic estimators are more robust to focusing artefacts but limited in resolution. Parametric tomographic estimators provide better vertical resolution but fail to adequately characterize continuously distributed volumetric scat-terers such as forest canopies. To overcome these limitations, this paper addresses a new wavelet-based sparse estimation method for 3D imaging and characterization for underfoliage objects. The effectiveness of this new approach is demonstrated by using L-band Multi-Baseline PolInSAR Data over Dornstetten, Germany.
Type de document :
Communication dans un congrès
IGARSS 2016 - IEEE International Geoscience and Remote Sensing Symposium, Jul 2016, Beijing, China. 2016
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https://hal.inria.fr/hal-01418435
Contributeur : Yue Huang <>
Soumis le : lundi 19 décembre 2016 - 12:10:17
Dernière modification le : vendredi 16 novembre 2018 - 01:29:37
Document(s) archivé(s) le : lundi 20 mars 2017 - 18:41:53

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  • HAL Id : hal-01418435, version 1

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Yue Huang, Jacques Levy Vehel, Laurent Ferro-Famil, Andreas Reigber. 3D imaging for underfoliage targets using L-band multibaseline polinsar data and sparse estimation methods. IGARSS 2016 - IEEE International Geoscience and Remote Sensing Symposium, Jul 2016, Beijing, China. 2016. 〈hal-01418435〉

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