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Phase unwrapping for phase imaging using the plug-and-play proximal algorithm.

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    This study introduces a robust plug-and-play proximal algorithm for phase unwrapping (PU), effectively removing noise during the process. The method ensures reliable phase reconstruction, even with high levels of noise in optical applications.

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    Area of Science:

    • Optical metrology
    • Image processing
    • Computational imaging

    Background:

    • Phase unwrapping (PU) is critical for quantitative analysis in optical applications.
    • Wrapped phase data, restricted to (-π, π], requires unwrapping to retrieve continuous phase information.
    • Challenges in PU include noise, undersampling, and calibration errors, leading to discontinuities.

    Purpose of the Study:

    • To develop a robust iterative method for 2D phase unwrapping.
    • To simultaneously address noise reduction during the phase unwrapping process.
    • To enhance phase reconstruction reliability in noisy environments.

    Main Methods:

    • Implementation of a plug-and-play (PnP) proximal algorithm for iterative phase unwrapping.
    • Formulation of a least-squares approach based on local phase differences.
    • Utilization of the fast cosine transform for solving subproblems within the PnP framework.

    Main Results:

    • Successful unwrapping of 2D phase data with simultaneous noise removal.
    • Demonstrated robustness of the PnP algorithm in high-noise scenarios.
    • Achieved reliable phase reconstruction despite significant measurement imperfections.

    Conclusions:

    • The proposed PnP iterative method offers a robust solution for phase unwrapping.
    • The technique effectively mitigates noise, improving the accuracy of phase reconstruction.
    • This approach enhances the applicability of phase unwrapping in challenging optical measurement conditions.