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Geometrical information based imaging of a high-contrast scattering object

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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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Dates and versions

hal-01235205 , version 1 (29-11-2015)

Identifiers

  • HAL Id : hal-01235205 , version 1

Cite

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