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Geometrical information based imaging of a high-contrast scattering object

Abstract : This paper is devoted to the resolution of an inverse scattering problem. Such problems are known to be highly nonlinear and ill-posed. In our case, the reconstruction is rendered all the more difficult by the high contrast: the physical characteristics of the scattering object greatly differ from those of the surrounding medium. To properly counterbalance the ill-posedness of the problem, an original shape model taking into account precise prior information about the geometry of the scattering object is proposed. Moreover, the scatterer shape is described with a reduced number of variables and the parametrization enables one to solve the inverse problem with a gradient-based algorithm. This contributes to reduce the computation cost. Tests conducted on synthetic datasets reveal good performance of the proposed algorithm, contrary to more classical approaches based on a Tikhonov regularization scheme or the use of an edge-preserving penalization function.
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Contributor : Denis Vautrin Connect in order to contact the contributor
Submitted on : Sunday, November 29, 2015 - 11:36:01 AM
Last modification on : Wednesday, April 27, 2022 - 3:50:03 AM
Long-term archiving on: : Friday, April 28, 2017 - 11:41:58 PM


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  • HAL Id : hal-01235205, version 1


Denis Vautrin, Jérôme Idier, Nicolas Paul. Geometrical information based imaging of a high-contrast scattering object. 2015. ⟨hal-01235205⟩



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