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Related Concept Videos

Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

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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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Updated: Mar 19, 2026

Digital Inline Holographic Microscopy DIHM of Weakly-scattering Subjects
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High-precision reconstruction algorithm for scanning white light interferometry based on region-directed high-density

Xiaoxiao Wei, Wenjun Lu, Pengshuo Fu

    Applied Optics
    |March 17, 2026
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    Summary
    This summary is machine-generated.

    This study introduces a new vertical scanning algorithm for white light interferometry to fix errors from vibrations and non-uniform sampling. The method improves 3D surface topography measurement accuracy and efficiency.

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    Area of Science:

    • Metrology
    • Optical Engineering
    • Surface Science

    Background:

    • Scanning white light interferometry (SWLI) is crucial for non-contact 3D surface topography measurement.
    • Accuracy in SWLI is often compromised by environmental vibrations and non-uniform sampling errors from scanning devices.

    Purpose of the Study:

    • To develop a robust vertical scanning algorithm for SWLI to compensate for non-uniform sampling errors.
    • To enhance the accuracy and efficiency of 3D surface topography measurements, especially for surfaces with large depth variations.

    Main Methods:

    • A region-directed high-density interpolation algorithm utilizing a high-precision grating ruler for accurate position labeling.
    • Coherence peak localization via the centroid method, followed by least-squares Fourier series fitting for waveform reconstruction.
    • Adaptive region of interest (ROI) segmentation for computational efficiency and invalid data elimination.

    Main Results:

    • Achieved a relative error of 0.484% for a 960 nm standard step measurement with a standard deviation of 3.046 nm.
    • Measurement error for large-depth steps was controlled within -0.3%.
    • ROI segmentation enhanced computational efficiency by approximately 44 times compared to global fitting.

    Conclusions:

    • The proposed algorithm effectively compensates for non-uniform sampling errors in SWLI.
    • It offers a feasible solution for high-precision batch measurement of surfaces with large-depth variations, demonstrating high accuracy, robustness, and efficiency.