基于FCM及快速迭代收缩阈值算法的平面ECT图像重建  

Planar ECT Image Reconstruction Based on FCM and Fast Iterative Shrinkage-thresholding Algorithm

作　　者：张立峰[1] 唐志浩 ZHANG Lifeng;TANG Zhihao(Department of Automation,North China Electric Power University,Baoding,Hebei 071003,China)

机构地区：[1]华北电力大学自动化系,河北保定071003

出　　处：《计量学报》2024年第6期899-906,共8页Acta Metrologica Sinica

基　　金：国家自然科学基金(61973115)。

摘　　要：为提高平面阵列电容成像系统的成像精度,提出一种基于模糊C均值聚类(FCM)进行数据优化的快速迭代收缩阈值算法(FISTA)。根据平面阵列电容数据的特点,首先利用FCM算法对测量电容值进行分类,保留有效电容值,实现电容向量降维;然后利用离散小波基(DWT)对灰度值进行稀疏表示,并建立L1正则化模型,采用FISTA进行求解,以实现图像重建;最后将FCM处理后的电容值分别用于Landweber算法、Tikhonov算法进行重建对比。仿真与实验结果表明,该算法重建图像的平均相对误差约为0.0527,平均相关系数约为0.9422,均优于其它算法,且重建图像伪影较少,更接近真实情况;因此,所提算法具有更好的重建效果。。To improve the imaging accuracy of planar array capacitive imaging systems,a fast iterative shrinkage-thresholding algorithm(FISTA)based on fuzzy C-means clustering(FCM)for data optimization is proposed.According to the characteristics of planar array capacitance data,firstly,FCM algorithm is used to classify the measured capacitance values,preserve the effective capacitance values,and achieve dimensionality reduction of the capacitance vector.Then,discrete wavelet bases(DWT)are used to sparsely represent gray values,and L1 regularization model is established to solve the problem using FISTA to achieve image reconstruction.Finally,the capacitance values processed by FCM are used for reconstruction comparison with Landweber algorithm and Tikhonov algorithm respectively.The simulation and experimental results show that the average relative error of the reconstructed image using the proposed algorithm is about 0.0527,and the average correlation coefficient is about 0.9422,both of which are superior to other algorithms.Moreover,the reconstructed image has fewer artifacts and is closer to the real situation.Therefore,the proposed algorithm has better reconstruction performance.

关 键 词：电容层析成像 平面阵列电容 图像重建 模糊C均值聚类 快速迭代收缩阈值算法 缺陷检测 

分 类 号：TB971[一般工业技术—计量学] TP212[机械工程—测试计量技术及仪器]