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Real-time ghost imaging algorithm on the multidimensional vector matrix Walsh transformation with spatiotemporal

Shengqi Feng, Aijun Sang, Xiaoni Li

    Applied Optics
    |January 16, 2024
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    This study introduces a novel algorithm for real-time ghost imaging, enabling adjustable frame rates and enhanced video quality for moving objects. The method overcomes DMD refresh rate limitations, improving visual comfort and smoothness.

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    Area of Science:

    • Computational imaging
    • Digital signal processing
    • Optics and photonics

    Background:

    • Real-time ghost imaging faces challenges with fixed frame rates and uneven speed, particularly for moving objects.
    • Existing methods are limited by display refresh rates, impacting video smoothness and user comfort.
    • Improving spatial information and temporal dynamics is crucial for comfortable, high-quality ghost imaging.

    Purpose of the Study:

    • To develop a real-time spatiotemporal algorithm for ghost imaging with adjustable frame rates and quality.
    • To address limitations of fixed frame rates and DMD refresh rates in ghost imaging of moving objects.
    • To enhance the visual comfort and smoothness of ghost imaging videos.

    Main Methods:

    • Utilized multidimensional vector matrix Walsh transform for image reconstruction.
    • Employed temporal and spatial correlations for free and adjustable video frame rates.
    • Applied spatial interpolation to enhance image detail and smoothness.
    • Developed adaptive parameterless evaluation algorithms (APEA and APVCEA) for objective and subjective video quality assessment.

    Main Results:

    • Achieved adjustable frame rates independent of DMD refresh rates.
    • Demonstrated improved ghost imaging video smoothness and visual comfort.
    • Increased Peak Signal-to-Noise Ratio (PSNR) by 12% objectively.
    • Enhanced structure retention by 13% and reduced Brisque by 70% subjectively.
    • Improved subjective video comfort by 14% compared to traditional methods.

    Conclusions:

    • The proposed algorithm effectively overcomes DMD refresh rate limitations in real-time ghost imaging.
    • The method significantly enhances ghost imaging video quality, smoothness, and user comfort.
    • The developed evaluation algorithms provide robust measures for image and video quality assessment.