基于全局变步长的傅里叶叠层显微成像重构算法

Fourier Ptychographic Microscopy Reconstruction Algorithm Based on Global Variable Step-Size

为了进一步提高重构算法的抗干扰能力和鲁棒性,提出了一种基于梯度下降法和牛顿法的全局法,并在此基础上,又提出了基于最优化理论的二分法与牛顿法两类变步长更新策略,使得迭代过程能够自主地选择最佳更新步长。为了充分利用顺序法和全局法各自的优势,制定终止判断准则使二者相结合。仿真和实验数据验证了所提算法的抗干扰能力优于各顺序法的结论,尤其当成像器件的噪声较大时,提出利用暗场图像信息来计算各阶梯度值的方法以减小噪声的影响。并且,上述方法只需要额外的3~5轮迭代过程即可得到满意的结果,时间仅增加了几秒钟。

To improve the anti-interference ability and robustness of the reconstruction algorithm,this paper proposes a global method based on the gradient descent and Newton methods and then proposes two types of variable step-size update strategies based on optimization theory,namely,the dichotomy and Newton methods,so that the iterative process can independently pick the best update step-size.To fully exploit the respective benefits of the sequential and global methods,the termination judgment criterion is designed to combine the two.The proposed algorithm’s anti-interference ability is demonstrated through simulation and experimental data to be superior to each sequential method.Especially when the noise of image devices is high,it is uniquely proposed to use dark field image information to calculate each gradient value,to minimize the impact of noise.Furthermore,the above methods only require additional 3‒5 rounds of an iterative process to achieve satisfactory results,and the time cost is only a few seconds.