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    This study introduces an adaptive phase retrieval algorithm to recover lost 3D shape data from saturated images in phase measuring profilometry (PMP). The method effectively reconstructs 3D shapes of high-reflection objects, improving industrial measurement accuracy.

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    Area of Science:

    • Optical Metrology
    • 3D Shape Measurement
    • Image Processing

    Background:

    • Phase measuring profilometry (PMP) is crucial for industrial 3D shape measurement.
    • Image saturation from high-reflection surfaces causes phase loss and 3D reconstruction errors in PMP.

    Purpose of the Study:

    • To develop an adaptive phase retrieval algorithm for accurate phase recovery in saturated regions.
    • To enable precise 3D reconstruction of high-reflection objects using PMP.

    Main Methods:

    • Identified saturated regions using minimum error thresholding.
    • Fused images with different exposures to locate fringe peak-valley coordinates.
    • Employed a least squares method and adaptive piecewise sine function for fringe pattern recovery.

    Main Results:

    • Successfully retrieved lost phase information from damaged sinusoidal fringes.
    • Achieved accurate 3D reconstruction of high-reflection objects.
    • The method requires only one or two images with varying exposure times.

    Conclusions:

    • The proposed adaptive algorithm effectively overcomes phase loss in PMP for reflective surfaces.
    • Offers advantages in operation time, system complexity, and hardware requirements.
    • Provides an effective industrial solution for 3D measurement of challenging objects.