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An image reconstruction algorithm for ECT using enhanced model and sparsity regularization

机译:使用增强型模型和稀疏正规化的ECT图像重建算法

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An image reconstruction algorithm for electrical capacitance tomography (ECT) using enhanced linear model and sparsity regularization (EMSR) is proposed in this paper. Compared to the traditional ECT linear model, the enhanced linear model takes the nonlinear effect of different capacitance groups and the sensitivity error into account. In addition, the sparsity of permittivity distributions under wavelet basis is investigated and utilized as the regularization term. The proposed algorithm using enhanced model and sparsity regularization is noted as EMSR and the performance is verified by using simulation data and experiment data. Both the simulation and experiment results indicate the potentiality of this method.
机译:本文提出了一种使用增强线性模型和稀疏正则化(EMSR)电容断层扫描(ECT)的图像重建算法。与传统的ECT线性模型相比,增强的线性模型采用不同电容组的非线性效果和考虑过敏误差。此外,对小波基础的介电常数分布的稀疏性进行了研究并用作正则化术语。使用增强型模型和稀疏正则化的所提出的算法被指出为EMSR,并且通过使用模拟数据和实验数据来验证性能。模拟和实验结果都表示该方法的潜力。

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