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Hybrid Iterative Reconstruction Method for Imaging Problems in ECT
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DOI：10.1109/TIM.2020.2987636.png)
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摘要
En 中文
As a powerful visualization tomography technique, electrical capacitance tomography (ECT) method, which reconstructs the permittivity distribution in a sensing domain according to the measured capacitance data, has been widely used in different industry scenarios. However, the image reconstruction in ECT is an ill-posed problem, and its application is plagued by low-quality reconstructions, and seeking for a robust algorithm to reduce reconstruction errors and artifacts is crucial. To increase the reconstruction quality, a novel cost function is built for imaging, in which the L1-2 norm is designed as a regularizer for encoding the sparsity prior of imaging objects. The ant lion optimizer (ALO) algorithm and the alternating direction method of multipliers (ADMMs) with the Douglas-Rachford splitting (DRS) method and the soft thresholding algorithm as powerful optimizers for minimizing the subproblems are combined into a novel solver for solving the built cost function more effectively. Simulation and experimental results indicate that the proposed imaging technique can improve the quality of reconstructed images.
Keyword:
Alternating direction method of multipliers (ADMMs)
ant lion optimizer (ALO)
image reconstruction
inverse problem
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期刊
IF:
5.9
论文数:
2.0W
被引数:
5.8W
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