Robust phase demodulation algorithm for single-frame interferogram

Wang, Nianfeng; Ma, Jun; Wei, Cong; Shen, Zhonghao; Liu, Wei; Yuan, Caojin

doi:10.1016/j.optlastec.2023.110463

Optics & Laser Technology

2024

DOI: 10.1016/j.optlastec.2023.110463

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Robust phase demodulation algorithm for single-frame interferogram

Nianfeng Wang,

Jun Ma,

Cong Wei

et al.

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2024

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Cited by 1 publication

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Single-frame interferogram phase retrieval using a phase-shifting generative adversarial network with physics-based fine-tuning

Shi,

Zhang,

Shao

et al. 2024

Appl. Opt.

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Phase retrieval from a single-frame interferogram is a challenge in optical interferometry. This paper proposes an accurate physics-based deep learning method for one-shot phase retrieval. This approach involves both data-driven pre-training of a phase-shifting network and subsequent model-driven fine-tuning. The well-designed pre-training network is capable of simultaneously generating π/2, π, and 3π/2 phase-shifted versions of the input interferogram to facilitate phase extraction. Moreover, integrating the interferometric model into the testing dataset enables self-supervised fine-tuning, optimizing the use of both data and physics-based priors. Simulations and experiments demonstrate the effectiveness of the proposed method in overcoming the common generalization limitation of data-driven models and achieving accurate phase retrieval. The proposed method not only enhances the accuracy of phase retrieval but also improves the generalization capability, making it robust under experimental conditions for interferometric applications.

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Single-frame interferogram phase retrieval using a phase-shifting generative adversarial network with physics-based fine-tuning

Shi,

Zhang,

Shao

et al. 2024

Appl. Opt.

View full text Add to dashboard Cite

show abstract

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Robust phase demodulation algorithm for single-frame interferogram

Cited by 1 publication

References 51 publications

Single-frame interferogram phase retrieval using a phase-shifting generative adversarial network with physics-based fine-tuning

Single-frame interferogram phase retrieval using a phase-shifting generative adversarial network with physics-based fine-tuning

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