摘要
电磁层析成像技术中图像重建算法的准确与快速是其在工业现场中得以应用的关键。Landweber迭代算法是电磁层析成像图像重建中应用最广泛的迭代算法,但其需要多次迭代,收敛速度慢。该文提出一种修正的Landweber迭代图像重建算法,该算法通过在构建的电磁层析成像逆问题目标泛函中添加正则化项,并采用自适应权重系数的方法,提高了收敛速度,并且改善了重建图像的质量。利用有限元法,在Maxwell中进行电磁层析成像正问题的求解,获得了图像重建所需的灵敏度矩阵。仿真和数值实验结果表明,修正的Landweber迭代算法在收敛速度和重建图像质量两方面均优于Landweber迭代算法。
The imaging speed and accuracy of image reconstruction algorithms in electromagnetic tomography are the keys to its application in industries. Landweber iteration algorithm is the most widely used iteration algorithm for image reconstruction of electromagnetic tomography, but it needs many iterations and has slow speed of convergence. A modified Landweber iteration algorithm was proposed through appending an additional regularization term into the constructed objective functional of the inverse problem of electromagnetic tomography and adopting adaptive weight coefficient method, which improves the speed of convergence and the quality of reconstructed image efficiently. Sensitivity matrix was obtained by using finite element method(FEM),which was conducted in Maxwell for the simulation of the forward problem of electromagnetic tomography. Both the simulation and numerical experiments results show that modified Landweber iteration algorithm is superior to Landweber iteration algorithm in the speed of convergence and quality of reconstructed image.
引文
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