首页|基于1-bit压缩感知非凸算法的平面ECT图像重建

基于1-bit压缩感知非凸算法的平面ECT图像重建

Planar ECT Image Reconstruction Based on 1-bit Compressed Sensing Non Convex Algorithm

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为提高平面电容成像系统的成像质量并提高重建速度,提出了一种基于 1-bit压缩感知(1-bit CS)非凸算法的平面ECT图像重建方法.首先,利用离散余弦基(DCT)对灰度值进行稀疏表示;其次,引入极大极小凹惩罚(MCP)作为正则化项,并建立 1-bit CS MCP正则化模型;然后,通过 MCP非凸算法迭代更新对偶解的近端算子,以求取最优对偶解;最后,根据对偶解求出重建灰度值并进行图像重建.仿真与实验结果表明,相比于Tikhonov算法、Landweber算法及传统压缩感知算法,所提方法得到的重建图像平均相对误差和相关系数分别为 0.049 6 和 0.943 5,平均重建时间约为 0.172 3 s,均优于其他 3 种算法,缺陷还原度及重建速度有明显提升.
In order to improve the imaging quality of planar capacitance imaging system,a planar ECT image reconstruction method based on 1-bit compressed sensing(1-bit CS)non convex algorithm is proposed.Firstly,discrete cosine basis(DCT)is used to sparsely represent grayscale values.Secondly,the maximum minimum concave penalty(MCP)is introduced as the regularization term,and the 1-bit CS MCP regularization model is established.Then,the near end operator of the dual solution is iteratively updated using the MCP non convex algorithm to obtain the optimal dual solution.Finally,calculate the reconstructed grayscale values based on the dual solution and perform image reconstruction.The simulation and experimental results show that compared with Tikhonov algorithm,Landweber algorithm and traditional compressed sensing algorithm,the average relative error and correlation coefficient of the reconstructed image obtained by the proposed method are 0.049 6 and 0.943 5 respectively,and the average reconstruction time is approximately 0.172 3 s,which is superior to the other three algorithms.The defect reduction degree and reconstruction speed have been significantly improved.

material defect detectionplanar electrical capacitance tomographyECT image reconstruction1-bit compressed sensingminimax concave penaltynon convex algorithm

唐志浩、张立峰

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华北电力大学 自动化系,河北 保定 071003

材料缺陷检测 平面电容成像 ECT图像重建 1-bit压缩感知 极大极小凹惩罚 非凸算法

2024

计量学报
中国计量测试学会

计量学报

CSTPCD北大核心
影响因子:0.303
ISSN:1000-1158
年,卷(期):2024.45(12)