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    This study introduces an adaptive filter to reduce noise in laser interferometer phase patterns, improving accuracy for detecting mechanical fatigue defects. The method effectively filters noise while preserving image details, outperforming existing techniques.

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    Area of Science:

    • Optical Metrology
    • Signal Processing
    • Materials Science

    Background:

    • Excessive noise in laser digital interferometry degrades phase unwrapping accuracy.
    • Noise hinders the reliable detection of mechanical fatigue defects from phase fringe patterns.

    Purpose of the Study:

    • To introduce an adaptive multidirectional frequency domain filtering method.
    • To effectively filter noise in wrapped phase patterns while preserving edge information.
    • To improve the accuracy of phase unwrapping and mechanical fatigue defect detection.

    Main Methods:

    • Developed an adaptive multidirectional frequency domain filtering technique.
    • Utilized the energy spectrum characteristics of localized wrapped phase patterns.
    • Automatically set the cutoff frequency for filtering.

    Main Results:

    • The proposed method effectively filters noise and preserves image edge information.
    • Experimental results show fewer residues compared to sine/cosine transform and multidirectional filtering.
    • Filtered images closely resemble noise-free images, demonstrating superior performance.

    Conclusions:

    • The adaptive multidirectional frequency domain filter is effective for noise reduction in laser interferometry.
    • This method enhances the accuracy of phase unwrapping and defect detection.
    • The technique offers a significant improvement over existing filtering methods for interferometric data.