Mr. Cong Li Profile

Cong Li

at Shenzhen Univ.

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Proceedings Article | 14 August 2019 Paper

A method for single image phase unwrapping based on generative adversarial networks

Cong Li, Yong Tian, Jingdong Tian

Proceedings Volume 11179, 1117911 (2019) https://doi.org/10.1117/12.2540155

KEYWORDS: Phase shift keying, Modulation, Computer simulations, Fourier transforms, Phase shifts, Data modeling, Image processing

Read Abstract +

Phase unwrapping technology plays an important role in phase measurement profilometry. The unwrapping results directly affect the measurement accuracy. With the development of deep learning theory, it is opening a new direction to phase unwrapping algorithm. In this paper, a new neural network model based on an improved generation adversarial network (iGAN) is proposed for phase unwrapping. Compared with traditional methods, it can effectively suppress the influence of noise such as shadows, and does not need any referenced grating information. In addition, it can realize the phase unwrapping with a single image. Specifically, the algorithm is verified by the three-dimensional reconstruction with structured light based on the simulation data. The results indicate that the proposed method can successfully unwrap the phase via a single image. It also can well suppress the influence of frequency and shadows.

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