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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.
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https://hal.inria.fr/hal-01418435
Contributor : Yue Huang <>
Submitted on : Monday, December 19, 2016 - 12:10:17 PM
Last modification on : Tuesday, October 6, 2020 - 3:09:53 AM
Long-term archiving on: : Monday, March 20, 2017 - 6:41:53 PM

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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. ⟨10.1109/igarss.2016.7729373⟩. ⟨hal-01418435⟩

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