基于L曲线法的超声CT正则化参数优化

超声逆散射成像图像重建反问题常常是不适定的。此种情况下,仅使用最小二乘法不能保证获得满意的介质分布图像重建结果,因此使用Tikhonov和TSVD正则化算法来产生适当的解。正则化参数的合适选取对图像重建至关重要,其对重建质量和计算速度都有影响,本文采用L-曲线准则确定相应的正则化参数。经实验验证:基于L-曲线法可以快速找到最优正则化参数,TSVD法与Tikhonov正则化方法相比,提高了图像重建质量,且适用范围广。

Regularization Parameter Optimum of Ultrasound CT Based on L Curve Method

Image reconstruction for Ultrasound inverse scattering imaging is an inverse problem anti is often ill posed. In such cases, only using simple least--squares method can not ensure a successful image reconstruction of media distribution. Therefore, Tikhonov regularization and TSVD regularization algorithm are employed to produce proper solutions. Correct selecting of regularization parameters is crucial for image reconstruction, which affects both quality and computation speed of the reconstruction. The corresponding regularization parameters are determined by adopting L-curve criterion in this paper. Simulation results show that based on L-curve method it can quickly find optimal regnlarization parameters, TSVD regularization method can improve the image reconstruction quality and its application field is larger than that of Tikhonov regularization method.