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Related Experiment Video

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Motion blur suppression method for time-of-flight imaging systems based on differential correlation sampling data.

Ping Song, Yunjian Bai, Chuangbo Hao

    Optics Express
    |September 23, 2025
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    This study introduces a novel method to reduce motion blur in Time-of-Flight (ToF) imaging systems. The technique effectively enhances image quality and accuracy for 3D measurements, even with system movement.

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    Area of Science:

    • Optics and Photonics
    • Computer Vision
    • Image Processing

    Background:

    • Time-of-Flight (ToF) imaging systems offer high frame rates, resolution, and cost-effectiveness.
    • Motion blur significantly degrades ToF ranging performance due to relative motion.
    • Existing methods struggle to effectively mitigate motion blur in dynamic ToF imaging scenarios.

    Purpose of the Study:

    • To develop and validate a novel motion blur suppression method for Time-of-Flight imaging systems.
    • To improve the ranging accuracy and image quality of ToF systems operating in dynamic environments.
    • To provide a robust solution for motion blur challenges in 3D measurement applications.

    Main Methods:

    • A three-step strategy is proposed: adaptive motion blur detection using noise levels, motion blur occurrence time determination and compensation with differential correlation sampling (DCS) data, and enhanced bilateral filtering based on spatial blur characteristics.
    • Adaptive thresholds are established for motion blur detection.
    • Compensation utilizes the complementary properties of DCS data to suppress blur.

    Main Results:

    • The proposed method significantly reduces the root mean squared error (RMSE) compared to existing techniques.
    • Key image quality metrics, including noise reduction ratio, peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM), are substantially enhanced.
    • Experimental validation in laboratory and real-world settings confirms the method's superiority.

    Conclusions:

    • The study presents a novel and effective framework for suppressing motion blur in ToF imaging systems.
    • The proposed method offers superior performance in reducing motion blur and improving image quality.
    • This research provides valuable insights into motion blur mitigation for 3D measurement systems.