An image reconstruction algorithm for electrical capacitance tomography based on robust principle component analysis.
An image reconstruction algorithm for electrical capacitance tomography based on robust principle component analysis.
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DOI：
10.3390/s130202076
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发表时间：
2013-02-05
期刊：
影响因子：
--
通讯作者：
Liu Q
中科院分区：
文献类型：
--
作者：
Lei J;Liu S;Wang X;Liu Q
电容层析成像（ECT）试图从电容测量数据中重建被测物体横截面的介电常数分布，其中重建算法在实际应用中起着至关重要的作用。本文基于鲁棒主成分分析（RPCA）方法，提出了一种利用多测量向量的动态重建模型，该模型将动态目标的演化过程视为与共同背景具有不同时间稀疏偏差的图像序列。提出了一种同时考虑时间约束和空间约束的目标函数，通过批处理模式对图像进行重构。针对所提出的目标泛函，提出了一种综合了交替方向迭代优化（ADIO）法和前向后分裂（FBS）法优点的迭代方案。通过数值仿真验证了该算法的可行性。
Electrical capacitance tomography (ECT) attempts to reconstruct the permittivity distribution of the cross-section of measurement objects from the capacitance measurement data, in which reconstruction algorithms play a crucial role in real applications. Based on the robust principal component analysis (RPCA) method, a dynamic reconstruction model that utilizes the multiple measurement vectors is presented in this paper, in which the evolution process of a dynamic object is considered as a sequence of images with different temporal sparse deviations from a common background. An objective functional that simultaneously considers the temporal constraint and the spatial constraint is proposed, where the images are reconstructed by a batching pattern. An iteration scheme that integrates the advantages of the alternating direction iteration optimization (ADIO) method and the forward-backward splitting (FBS) technique is developed for solving the proposed objective functional. Numerical simulations are implemented to validate the feasibility of the proposed algorithm.
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