1 国科大杭州高等研究院物理与光电工程学院，浙江 杭州 310024
2 中国科学院上海光学精密机械研究所信息光学与光电技术实验室，上海 201800
深度学习已逐步深入多个光学技术领域，推动了诸多光学技术的发展。同时，航空航天观测、AR/VR消费电子、手机摄影、超短焦投影仪等产业快速发展，对光学系统提出了更高、更复杂的设计需求。这些光学系统对性能的高要求，使得光学元件面形的复杂度相应提高。因此，传统的设计方法面临巨大挑战。深度学习具有强大的运算、数据演化和非线性逆问题求解能力，为更复杂的光学系统设计优化求解提供了新思路、新方法。随着对光学系统性能的要求越来越高，自由曲面、超构表面等新型光学元件的需求大大增加，为光学系统提供了更大的发展潜力和想象空间。早期的迭代优化和直接求解的光学设计方法不再适用，光学设计方法向更高难度的数学求解方向发展。得益于人工智能技术软硬件的发展，光学系统设计方法也跨入新的时代——人工智能光学设计时代。从传统迭代优化到人工智能，光学系统设计方法并不能割裂地突跃式发展。本文系统性地论述了光学系统设计方法的内在路径联系与发展逻辑，并对未来的发展方向进行了展望。
光学设计 人工智能 深度学习 迭代优化 中国激光
2023, 50(11): 1101012
Author Affiliations
Abstract
1 School of Electronic Engineering and Optoelectronic Technology, Nanjing University of Science and Technology, Nanjing 210094, China
2 MIIT Key Laboratory of Advanced Solid Laser, Nanjing University of Science and Technology, Nanjing 210094, China
3 Department of Material Science and Engineering, University of California Los Angeles, Los Angeles, CA 90095, USA
Currently, it is generally known that lens-free holographic microscopy, which has no imaging lens, can realize a large field-of-view imaging with a low-cost setup. However, in order to obtain colorful images, traditional lens-free holographic microscopy should utilize at least three quasi-chromatic light sources of discrete wavelengths, such as red LED, green LED, and blue LED. Here, we present a virtual colorization by deep learning methods to transfer a gray lens-free microscopy image into a colorful image. Through pairs of images, i.e., grayscale lens-free microscopy images under green LED at 550 nm illumination and colorful bright-field microscopy images, a generative adversarial network (GAN) is trained, and its effectiveness of virtual colorization is proved by applying it to hematoxylin and eosin stained pathological tissue samples imaging. Our computational virtual colorization method might strengthen the monochromatic illumination lens-free microscopy in medical pathology applications and label staining biomedical research.
lens-free microscopy deep learning digital holography virtual colorization Chinese Optics Letters
2020, 18(12): 121705
