迭代重建
代数重建技术
奇异值分解
电极
算法
共轭梯度法
图像质量
激发
重建算法
人工智能
计算机视觉
计算机科学
图像(数学)
材料科学
物理
工程类
电气工程
量子力学
作者
Zhen Xu,Junchao Huang,Yandan Jiang,Baoliang Wang,Zhiyao Huang,Manuchehr Soleimani
出处
期刊:IEEE Transactions on Instrumentation and Measurement
[Institute of Electrical and Electronics Engineers]
日期:2021-01-01
卷期号:70: 1-11
被引量:13
标识
DOI:10.1109/tim.2021.3098388
摘要
An image reconstruction algorithm, which is developed for a 12-electrode capacitively coupled electrical resistance tomography (CCERT) system under 2-electrode excitation strategy, is proposed. Based on L-curve and Reginska's method, truncated singular value decomposition (TSVD) is used to reconstruct the initial image. The algebraic reconstruction technique (ART) algorithm is used to obtain the final reconstructed image. Image reconstruction experiments are conducted by a 12-electrode CCERT system. The proposed algorithm (TSVD + ART) is compared with conventional linear back projection (LBP), Tikhonov, Landweber, ART, simultaneous iterative reconstruction technique (SIRT), total variation (TV), conjugate gradient (CG), and TSVD to evaluate its image reconstruction performance. Image reconstruction results show the proposed algorithm (TSVD + ART) can effectively exploit the advantages of 2-electrode excitation strategy and hence realize higher quality image reconstruction. Under 2-electrode excitation strategy, the proposed algorithm has an obvious advantage over conventional image reconstruction algorithms. Under 1-electrode excitation strategy, the image reconstruction performance is comparable or slightly improved compared with that of conventional image reconstruction algorithms. Image reconstruction results also indicate the TSVD is effective to obtain the initial reconstructed image. The quality of the initial reconstructed image can be significantly improved compared with that of classic LBP, either under 2-electrode excitation strategy or 1-electrode excitation strategy.
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