In this paper we give new insights into quantitative microwave tomography with robust Huber regularizer and Gauss-Newton optimization. Firstly, we validate this approach for the first time on real electromagnetic measurements. Secondly, we extend the …
Reconstruction of inhomogeneous dielectric objects from microwave scattering is a nonlinear and ill-posed inverse problem. In this communication, we develop a new class of weakly convex discontinuity adaptive (WCDA) models as a regularization for …
We develop a new regularization approach for 3D quantitative microwave tomography, based on a discontinuity adaptive model. The resulting reconstructions from sparse data points for 3D piecewise constant objects are encouraging. The reconstructions …
We develop a new regularization method for quantitative microwave tomography, based on a discontinuity adaptive Markov random Field model. The results on 2D data sets are encouraging and indicate potential for use in biomedical imaging.