摄影术
计算机科学
吞吐量
相位恢复
实施
斑点图案
傅里叶变换
计算机视觉
视野
计量学
人工智能
编码孔径
光学
物理
衍射
探测器
电信
程序设计语言
无线
量子力学
作者
Guoan Zheng,Cheng Shen,Shaowei Jiang,Pengming Song,Changhuei Yang
标识
DOI:10.1038/s42254-021-00280-y
摘要
The competition between resolution and the imaging field of view is a long-standing problem in traditional imaging systems — they can produce either an image of a small area with fine details or an image of a large area with coarse details. Fourier ptychography (FP) is an approach for tackling this intrinsic trade-off in imaging systems. It takes the challenge of high-throughput and high-resolution imaging from the domain of improving the physical limitations of optics to the domain of computation. It also enables post-measurement computational correction of optical aberrations. We present the basic concept of FP, compare it to related imaging modalities and then discuss experimental implementations, such as aperture-scanning FP, macroscopic camera-scanning FP, reflection mode, single-shot set-up, X-ray FP, speckle-scanning scheme and deep-learning-related implementations. Various applications of FP are discussed, including quantitative phase imaging in 2D and 3D, digital pathology, high-throughput cytometry, aberration metrology, long-range imaging and coherent X-ray nanoscopy. A collection of datasets and reconstruction codes is provided for readers interested in implementing FP themselves. Fourier ptychography is an imaging approach that addresses the intrinsic trade-off between resolution and field of view in optical systems and provides computational correction of optical aberrations. This Technical Review surveys its implementations and applications.
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