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    This study introduces a fast and memory-efficient Non-Line-of-Sight (NLOS) imaging algorithm using phasor field-diffraction. It significantly reduces reconstruction time and memory usage for enhanced real-time NLOS imaging capabilities.

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    Area of Science:

    • Computational imaging
    • Optics and photonics
    • Computer vision

    Background:

    • Non-Line-of-Sight (NLOS) imaging enables visualization of occluded scenes via indirect diffuse reflections.
    • Current NLOS reconstruction algorithms face challenges in real-time application due to high computational and memory demands.

    Purpose of the Study:

    • To develop a computationally efficient and memory-saving algorithm for NLOS reconstruction.
    • To enable real-time implementation of NLOS imaging.

    Main Methods:

    • A novel phasor field-diffraction-based NLOS reconstruction algorithm is proposed.
    • Utilizes the radial property of Rayleigh Sommerfeld diffraction (RSD) kernels and Fourier transform linearity.
    • Reconstructs Fourier domain representations of RSD kernels using kernel bases, optimized by radial sampling and runtime construction.

    Main Results:

    • Achieves significant memory efficiency improvement, up to 220× compared to original RSD algorithms.
    • Demonstrates a substantial reduction in reconstruction time.
    • Maintains high imaging quality with minimal impact.

    Conclusions:

    • The proposed algorithm offers a practical solution for real-time NLOS imaging.
    • Provides a significant advancement in computational efficiency and memory management for NLOS reconstruction.