Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB, R3T5V6, Canada.
IEEE Trans Med Imaging. 2009 Dec;28(12):2015-9. doi: 10.1109/TMI.2009.2027703. Epub 2009 Jul 24.
Although Krylov subspace methods provide fast regularization techniques for the microwave imaging problem, they cannot preserve the edges of the object being imaged and may result in an oscillatory reconstruction. To suppress these spurious oscillations and to provide an edge-preserving regularization, we use a multiplicative regularizer which improves the reconstruction results significantly while adding little computational complexity to the inversion algorithm. We show the inversion results for a real human forearm assuming the 2-D transverse magnetic illumination and a cylindrical object assuming the 2-D transverse electric illumination.
虽然 Krylov 子空间方法为微波成象问题提供了快速的正则化技术，但它们不能保留被成象物体的边缘，并且可能导致重建结果的振荡。为了抑制这些虚假的振荡并提供边缘保持正则化，我们使用乘法正则化器，它在为反演算法增加很少的计算复杂度的同时，显著改善了重建结果。我们展示了对一个真实的人类前臂的反演结果，假设二维横向磁场照明，以及对一个圆柱形物体的反演结果，假设二维横向电场照明。
