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A Bayesian-Compressive-Sampling-Based Inversion for Imaging Sparse Scatterers

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3 Author(s)
Oliveri, G. ; Dept. of Inf. Eng. & Comput. Sci., ELEDIA Res. Group, Univ. of Trento, Trento, Italy ; Rocca, P. ; Massa, A.

In this paper, a new approach based on the Bayesian compressive sampling (BCS ) and within the contrast source formulation of an inverse scattering problem is proposed for imaging sparse scatterers. By enforcing a probabilistic hierarchical prior as a sparsity regularization constraint, the problem is solved by means of a fast relevance vector machine. The effectiveness and robustness of the BCS-based approach are assessed through a set of numerical experiments concerned with various scatterer configurations and different noisy conditions.

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Geoscience and Remote Sensing, IEEE Transactions on  (Volume:49 ,  Issue: 10 )