Simulation study of EIT inverse problem based on Bayesian method

Ying Li, Huifang Zhao,Renjie He,Liyun Rao,XueQin Shen,Weili Yan,Dirar S. Khoury,Lijie Feng,Jie Hong,Hongbin Wang,Guizhi Xu

Electromagnetic Field Computation（2010）

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Abstract

The prior of blocky resistivity profile is formulated based on the minimal of total variation using Bayesian method, and the resistivity distribution is reconstructed by Maximum a posteriori (MAP). The Markov chain Monte Carlo (MCMC) method with Gibbs sampler is used to sample from posterior density. The simulations on the 2D model show the feasibility of the method.

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Key words

gibbs sampler,bayesian method,bayes methods,posterior density,inverse problems,eit inverse problem,blocky resistivity profile,markov chain monte carlo method,monte carlo methods,markov processes,electric impedance imaging,bayesian methods,impedance,tomography,total variation,conductivity,electromagnetic fields,inverse problem,markov chain monte carlo,image reconstruction

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