Appl Opt. 2023 Apr 1;62(10):2617-2628. doi: 10.1364/AO.480923.
Lensless systems based on ptychographic imaging can simultaneously achieve a large field of view and high resolution while having the advantages of small size, portability, and low cost compared to traditional lensed imaging. However, lensless imaging systems are susceptible to environmental noise and have a lower resolution of individual images than lens-based imaging systems, which means that they require a longer time to obtain a good result. Therefore, in this paper, to improve the convergence rate and robustness of noise in lensless ptychographic imaging, we propose an adaptive correction method, in which we add an adaptive error term and noise correction term in lensless ptychographic algorithms to reach convergence faster and create a better suppression effect on both Gaussian noise and Poisson noise. The Wirtinger flow and the Nesterov algorithms are used in our method to reduce computational complexity and improve the convergence rate. We applied the method to phase reconstruction for lensless imaging and demonstrated the effectiveness of the method by simulation and experiment. The method can be easily applied to other ptychographic iterative algorithms.
无透镜系统基于相衬成像，可以在具有尺寸小、便携性和低成本等优点的同时，实现大视场和高分辨率，相比于传统的透镜成像。然而，无透镜成像系统容易受到环境噪声的影响，并且单个图像的分辨率比基于透镜的成像系统低，这意味着它们需要更长的时间才能获得良好的结果。因此，在本文中，为了提高无透镜相衬成像中噪声的收敛速度和鲁棒性，我们提出了一种自适应校正方法，在该方法中，我们在无透镜相衬算法中添加了自适应误差项和噪声校正项，以更快地达到收敛，并对高斯噪声和泊松噪声都有更好的抑制效果。我们在方法中使用 Wirtinger 流和 Nesterov 算法来降低计算复杂度并提高收敛速度。我们将该方法应用于无透镜成像的相位重建，并通过仿真和实验验证了该方法的有效性。该方法可以很容易地应用于其他相衬迭代算法。
