Work

Quantitative phase imaging in dual-wavelength interferometry using a single wavelength illumination and deep learning

Year: 2020

Type: article

Abstract: In this manuscript, we propose a quantitative phase imaging method based on deep learning, using a single wavelength illumination to realize dual-wavelength phase-shifting phase recovery. By using the conditional generative adversarial network (CGAN), from one interferogram recorded at a single wavelength, we obtain interferograms at other wavelengths, the corresponding wrapped phases and then the phases at synthetic wavelengths. The feasibility of the proposed method is verified by simulation and experiments. The results demonstrate that the measurement range of single-wavelength interferometry (SWI) is improved by keeping a simple setup, avoiding the difficulty caused by using two wavelengths simultaneously. This will provide an effective solution for the problem of phase unwrapping and the measurement range limitation in phase-shifting interferometry.

Source: Optics Express

DOI: 10.1364/oe.402808

Authors: Jiaosheng Li, Qinnan Zhang, Liyun Zhong, Jindong Tian, Giancarlo Pedrini, Xiaoxu Lu

Institutions: South China Normal University, Shenzhen University, University of Stuttgart

Language: English

Topic: Optical measurement and interference techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,270

Funders: National Natural Science Foundation of China, China Postdoctoral Science Foundation