基于改进正问题模型和模因算法的ECT图像重建

ECT image reconstruction based on improved forward problem model and memetic algorithm

为提高电容层析成像的图像重建质量,提出了一种基于改进正问题模型和模因算法的图像重建算法,即Im-MA算法。通过对灵敏度矩阵进行平滑滤波和降维处理,改进正问题模型。使用L_(2)范数作为数据拟合的测度,并将全变差作为正则项,构建目标函数,将图像重建问题转化为最优化问题。采用麻雀搜索算法和天牛须搜索算法相结合的模因(memetic algorithm,MA)算法求解目标函数。仿真与实验结果表明:与常用的Landweber算法相比,Im-MA算法的重建误差更小,且重建图像与真实分布更加接近。Im-MA算法为解决ECT逆问题提供了一种有效的新方法。

In order to improve the image reconstruction quality of electrical capacitance tomography(ECT),an image reconstruction algorithm based on an improved forward problem model and a memetic algorithm,abbreviated as Im-MA algorithm,was proposed.The forward problem model was improved by utilizing smooth filtering and dimension reduction of the sensitivity matrix.An objective function was constructed to transform the image reconstruction problem into an optimization problem by using the L_(2)norm as data fitting measurement and the total variation as regular term.The objective function was solved by using the memetic algorithm formulated by the combination of sparrow search algorithm and beetle antenna search algorithm.Simulation and experimental results show that the reconstruction error of the Im-MA algorithm is smaller,compared with the commonly used Landweber algorithm,and its reconstructed image is much closer to the real distribution.The Im-MA algorithm provides an effective new way to solve the ECT inverse problem.