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首页> 外文会议>Instrumentation and Measurement Technology Conference (I2MTC), 2012 IEEE International >A shrinkage-thresholding method for the inverse problem of Electrical Resistance Tomography
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A shrinkage-thresholding method for the inverse problem of Electrical Resistance Tomography

机译：电阻层析成像反问题的收缩阈值法

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摘要

Image reconstruction for Electrical Resistance Tomography (ERT) is an ill-posed nonlinear inverse problem. Considering the influence of the sparse measurement data on the quality of the reconstructed image, the l1-regularized least-squares program (l1 regularized LSP) is introduced to solve the inverse problem in this paper. To meet the need of high speed in ERT, the fast iterative shrinkage-thresholding algorithm (FISTA) is employed for image reconstruction in our work. Simulation results of the FISTA and l1_ls algorithm show that the l1 regularized LSP is superior to the l2 regularization method, especially in avoiding the over-smoothing of the reconstructed image. In addition, to improve the convergence speed and imaging quality in FISTA algorithm, the initial guess is calculated with the conjugate gradient method. Comparative simulation results demonstrate the feasibility of FISTA in ERT system and its advantage over the l1_ls regularization method.
机译：电阻层析成像（ERT）的图像重建是一个不适定的非线性逆问题。考虑到稀疏测量数据对重建图像质量的影响，本文引入了l1正则化最小二乘程序（l1正则化LSP）来解决反问题。为了满足ERT中对高速的需求，我们在工作中采用了快速迭代收缩阈值算法（FISTA）进行图像重建。 FISTA和l1_ls算法的仿真结果表明，l1正则化的LSP优于l2正则化的方法，特别是在避免重构图像过度平滑的情况下。另外，为了提高FISTA算法的收敛速度和成像质量，采用共轭梯度法计算初始猜测。对比仿真结果证明了FISTA在ERT系统中的可行性及其相对于l1_ls正则化方法的优势。

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