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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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Related Experiment Video

Updated: Oct 17, 2025

Characterization of Surface Modifications by White Light Interferometry: Applications in Ion Sputtering, Laser Ablation, and Tribology Experiments
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Phase-error-compensation-based surface recovery algorithm using spectrum selection for white light interferometry.

Long Ma, Yuan Zhao, Mei-Ye Du

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    |October 6, 2021
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    Summary
    This summary is machine-generated.

    This study introduces a novel white light interferometry algorithm for enhanced surface recovery. The method effectively separates and reduces phase noise, improving topographic measurement accuracy and robustness.

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    Area of Science:

    • Optical Metrology
    • Surface Characterization
    • Signal Processing

    Background:

    • White light interferometry (WLI) is a standard technique for non-contact surface profiling.
    • Existing WLI methods can be susceptible to phase errors and noise, affecting measurement accuracy.
    • Signal processing in WLI often requires careful calibration and can be sensitive to environmental factors.

    Purpose of the Study:

    • To propose a new white light signal processing algorithm for improved surface recovery.
    • To develop a phase error compensation method utilizing spectrum selection.
    • To enhance the accuracy and robustness of topographic measurements using WLI.

    Main Methods:

    • A novel WLI signal processing algorithm is developed for phase error compensation.
    • The algorithm models nonlinear phase distribution as random errors and systemic deviations.
    • Spectrum selection and analysis of white light sources (LEDs, halogen lamps) are performed.
    • A coefficient based on inner products of selected spectral points evaluates phase map linearity.
    • Optimal spectrum ranges are identified for maximal measurement performance.

    Main Results:

    • The proposed algorithm effectively separates and attenuates phase noise from the linear phase map.
    • Simulations demonstrate reduced disturbance in recovered topography under various noise levels (SNR, scan step).
    • Experimental calibration using a step height standard yielded high repeatability (0.44 nm).
    • Validation with silicon wafers and roughness standards confirmed the method's robustness.

    Conclusions:

    • The developed algorithm offers significant improvements in phase noise reduction for WLI.
    • Spectrum selection is a viable strategy for optimizing WLI performance and accuracy.
    • The method shows promise for precise surface recovery in demanding metrology applications.