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Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
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Robust phase unwrapping algorithm for noisy and segmented phase measurements.

Yi Zong, Mingliang Duan, Caiyun Yu

    Optics Express
    |October 7, 2021
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    Summary

    A novel robust phase unwrapping algorithm (RPUA) effectively handles noise and segmented phase data. This advanced method ensures accurate phase unwrapping, demonstrating high robustness and practical applicability in various experimental conditions.

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    Area of Science:

    • Signal Processing
    • Image Analysis
    • Metrology

    Background:

    • Phase unwrapping is critical in various imaging and measurement techniques.
    • Conventional algorithms struggle with noisy and segmented phase data, leading to errors.
    • Existing methods often fail to address challenges like phase aliasing and isolated phase regions.

    Purpose of the Study:

    • To introduce a robust phase unwrapping algorithm (RPUA) capable of overcoming noise and segmentation issues.
    • To develop a method that provides accurate phase unwrapping in challenging data conditions.
    • To demonstrate the practical utility of the proposed algorithm in real-world applications.

    Main Methods:

    • A novel phase derivative model combined with error-correction iterations for noise reduction.
    • Spatial domain phase island bridging using numerical carrier frequency and fringe extrapolation.
    • Elimination of height faults to enable segmented phase unwrapping.

    Main Results:

    • Numerical simulations confirmed superior robustness and efficiency compared to three conventional methods.
    • Experimental validation showed accurate unwrapped phase retrieval under varying noise levels.
    • The RPUA successfully processed segmented phases, demonstrating reliable practicality.

    Conclusions:

    • The proposed robust phase unwrapping algorithm (RPUA) offers significant improvements in handling noisy and segmented phase data.
    • RPUA demonstrates high accuracy, robustness, and efficiency, making it suitable for demanding applications.
    • The algorithm's ability to process segmented phases indicates its broad practical applicability in metrology and imaging.