Long-Distance Sub-Diffraction High-Resolution Imaging Using Sparse Sampling

Abstract

How to perform imaging beyond the diffraction limit has always been an essential subject for the research of optical systems. One effective way to achieve this purpose is Fourier ptychography, which has been widely used in microscopic imaging. However, microscopic imaging measurement technology cannot be directly extended to imaging macro objects at long distances. In this paper, a reconstruction algorithm is proposed to solve the need for oversampling low-resolution images, and it is successfully applied to macroscopic imaging. Compared with the traditional FP technology, the proposed sub-sampling method can significantly reduce the number of iterations in reconstruction. Experiments prove that the proposed method can reconstruct low-resolution images captured by the camera and achieve high-resolution imaging of long-range macroscopic objects.

Depth-based defocus elimination for macroscopic Fourier ptychography imaging

“…Many studies on the macroscopic FP improve the reconstruction efficiency through the algorithm of iterations and deep learning. [6,7] These methods are all aimed at the imaging resolution of planar patterns such as a plate target. However, there is no analyzation for three-dimensional real scenes, which means that there are normally multiple objects in an imaging scene and there is a certain distance between these objects.…”

Deep Multi-Feature Transfer Network for Fourier Ptychographic Microscopy Imaging Reconstruction

“…Although the traditional imaging mechanism is simple and easy to implement, it still faces many bottleneck problems. It is difficult to solve the challenges brought by the new application requirements [ 1 , 2 ]. Fourier ptychographic microscopy is an imaging technology with large field of view, high resolution and quantitative phase calculation developed in recent years [ 3 , 4 , 5 ].…”