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Simplified phase-recovery method in temporal speckle pattern interferometry.

Pablo Etchepareborda, Arturo Bianchetti, Ana Laura Vadnjal

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    Summary
    This summary is machine-generated.

    A simplified method simplifies object phase recovery in temporal speckle pattern interferometry using a temporal carrier and bivariate empirical mode decomposition, avoiding Hilbert transforms for improved analysis.

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    Area of Science:

    • Optical Metrology
    • Interferometry
    • Signal Processing

    Background:

    • Temporal speckle pattern interferometry (TSPI) is a powerful technique for non-contact measurement.
    • Traditional phase recovery methods can be sensitive to noise and signal fluctuations.
    • The Hilbert transform, commonly used in phase retrieval, is unsuitable for signals with abrupt changes.

    Purpose of the Study:

    • To develop a simplified and robust method for object phase recovery in TSPI.
    • To analyze the spatiotemporal evolution of object phase using a novel decomposition framework.
    • To compare the proposed method's performance against existing phase-retrieval techniques.

    Main Methods:

    • Implementation of a simplified phase recovery method in TSPI utilizing a temporal carrier.
    • Modulation of interferometric intensity signals with a known temporal carrier.
    • Analysis using a bivariate empirical mode decomposition (BEMD) framework, avoiding the Hilbert transform.

    Main Results:

    • Successful isolation of the object phase's spatiotemporal evolution.
    • Demonstration of the BEMD framework's suitability for intensity signals with abrupt fluctuations.
    • Comparative analysis showing competitive computation time and phase recovery capability against established methods via simulations and experimental data.

    Conclusions:

    • The proposed simplified method offers an effective alternative for object phase recovery in TSPI.
    • Bivariate empirical mode decomposition provides a robust approach for analyzing modulated interferometric signals.
    • The technique demonstrates practical advantages in terms of computational efficiency and accuracy.