基于压缩感知的电容层析成像图像重建算法

发布时间：2018-06-01 16:17

本文选题：电容层析成像 + 图像重建　；参考：《电子学报》2017年02期

【摘要】：为提高电容层析成像(ECT)系统采样速率及重建图像质量,本文提出一种基于压缩感知理论的ECT图像重建算法.首先,应用离散Fourier变换基将原始图像灰度信号进行稀疏化处理;接着,从16电极ECT系统中随机选取14个电极按随机顺序进行激励,并按随机顺序测量不同电极之间电容值,得到测量电容信号并建立相应的观测矩阵;最后,采用L1范数正则化模型和原对偶内点法实现图像重建.仿真实验结果表明,基于压缩感知理论算法重建的图像其质量优于Landweber迭代算法,在节省采样时间的同时可实现较高精度的图像重建,为ECT图像重建的研究提供了一种新的手段.
[Abstract]:In order to improve the sampling rate and image quality of electrical capacitance tomography (ECT) system, a ECT image reconstruction algorithm based on compression sensing theory is proposed in this paper. Firstly, the original image gray signal is sparse based on discrete Fourier transform, then 14 electrodes are randomly selected from the 16-electrode ECT system to be excited in random order, and the capacitance between different electrodes is measured in random order. The capacitance signal is measured and the corresponding observation matrix is established. Finally, the L1 norm regularization model and the original dual interior point method are used to reconstruct the image. The simulation results show that the quality of the reconstructed image based on the compression perception theory is better than that of the Landweber iterative algorithm, which can save sampling time and achieve high precision image reconstruction, which provides a new method for the research of ECT image reconstruction.
【作者单位】：华北电力大学自动化系;
【基金】：国家自然科学基金(No.51306058) 中央高校基本科研业务费专项(No.2014MS142)
【分类号】：TP391.41

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