Y4-Net: a deep learning solution to one-shot dual-wavelength digital holographic reconstruction

被引：65
|
作者：
Wang, Kaiqiang [1 ]
Qian Kemao [2 ]
Di, Jianglei [1 ]
Zhao, Jianlin [1 ]
机构：
[1] Northwestern Polytech Univ, Sch Phys Sci & Technol, MOE Key Lab Mat Phys & Chem Extraordinary Condit, Shaanxi Key Lab Opt Informat Technol, Xian 710129, Peoples R China
[2] Nanyang Technol Univ, Sch Comp Sci & Engn, Singapore 639798, Singapore
来源：
OPTICS LETTERS | 2020年 / 45卷 / 15期
基金：
中国国家自然科学基金;
关键词：
MICROSCOPY;
D O I：
10.1364/OL.395445
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
In this Letter, a deep learning solution (Y4-Net, four output channels network) to one-shot dual-wavelength digital holography is proposed to simultaneously reconstruct the complex amplitude information of both wavelengths from a single digital hologram with high efficiency. In the meantime, by using single-wavelength results as network ground truth to train the Y4-Net, the challenging spectral overlapping problem in common-path situations is solved with high accuracy. (C) 2020 Optical Society of America
引用
收藏
页码：4220 / 4223
页数：4
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