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    Area of Science:

    • Optical Metrology
    • Image Processing
    • Computational Physics

    Background:

    • Phase unwrapping is critical in optical metrology but challenging with high noise and fringe densities.
    • Existing pre-filtering methods can introduce artifacts, complicating accurate phase retrieval.
    • Speckle decorrelation noise in holographic data poses a significant challenge for robust unwrapping.

    Purpose of the Study:

    • To develop a robust phase unwrapping algorithm capable of handling high noise levels and fringe densities.
    • To address the limitations of traditional pre-filtering techniques in holographic phase data processing.
    • To provide an effective solution for accurate phase retrieval in digital holographic metrology.

    Main Methods:

    • A novel calibration method for the first-order spatial phase derivative is proposed.
    • An iterative approach is employed, considering the influence of noise on wrapped data.
    • The algorithm is validated using realistic numerical simulations with varying noise and fringe densities.

    Main Results:

    • The proposed method successfully unwraps holographic phase data corrupted by non-Gaussian speckle decorrelation noise.
    • Simulations demonstrate superior accuracy and reduced computation time compared to established algorithms.
    • The algorithm shows robustness even with progressively increased fringe density and noise standard deviation.

    Conclusions:

    • The developed phase unwrapping algorithm is robust and effective for noisy holographic data.
    • It offers practical advantages in digital holographic metrology due to its speed and accuracy.
    • The method overcomes limitations of existing techniques, enabling reliable phase retrieval in challenging conditions.