Weigthing hyperparameters for 3D Bayesian estimation in Eddy current tomography

The skin effect is a major limitation for Eddy Current Tomography ECT. It limits its ability to image flaws inside electricaly conductive material. In this paper we tackle the inverse problem in a Bayesian framework which imply the computation of the hyperparameters defining the weight of the a priori in the estimate. To improve its performance regarding buried flaws, we suggest that hyperparameters of the inverse problem can´t be the same for each layer of discretization and we propose a method to bias them accordingly to the skin effect.