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Bayesian Regularization in Nonlinear Imaging: Reconstructions From Experimental Data in Nonlinearized Microwave Tomography

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3 Author(s)
Roberta Autieri ; Department of Technology (DiT), Università degli Studi Parthenope di Napoli, Napoli, Italy ; Giancarlo Ferraiuolo ; Vito Pascazio

In this paper, we investigate the robustness and the effectiveness of a microwave imaging technique, based on the Bayesian estimation theory, for the reconstruction of dielectric profiles. The method has been applied and validated on real experimental data. Our statistical-based inversion algorithm takes advantage of Bayesian regularization, which permits the inversion of a strongly nonlinear model using a Markov random field as an a priori statistical model of the unknown image. Such choice leads to a robust and effective nonlinear inversion method. The exhaustive analysis performed on the experimental data shows the good performance of the method.

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IEEE Transactions on Geoscience and Remote Sensing  (Volume:49 ,  Issue: 2 )