基于MCMC方法的电容成像图像重构算法

研究基于概率统计的电容成像图像重构算法,以马尔科夫随机场的方式给出介电常数分布的先验概率,利用电容成像(electrical capacitance tomography,ECT)线性模型得到似然函数,通过马尔科夫链蒙特卡罗(Markov chain Monte Carlo,MCMC)方法对介电常数分布的后验概率密度进行采样,马尔科夫链的转移核利用Metropolis-Hastings方法得到,结合嵌套迭代提高计算效率。仿真结果表明,嵌套迭代-MCMC方法在正则化参数设置合适的条件下,可以得到较好的图像质量,基于MCMC方法图像重构算法为解决ECT图像重构问题提供一种新思路。

Markov chain Monte Carlo (MCMC) based image reconstruction algorithm for electrical capacitance tomography

An image reconstruction algorithm based on statistical model for electrical capacitance tomography(ECT) is proposed.The prior probability and likelihood function are obtained using multi-level Markov random field and ECT liner model.Using MCMC sampling,the posterior distribution of permittivity is estimated.Meanwhile,nested iteration is introduced to improve the calculation efficiency.Simulation results show that the nested iteration-MCMC can enhance the calculation speed significantly and provide reconstruction images with higher quality if a proper regularization parameter is used.The MCMC based method provides a new way for ECT image reconstruction.