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Updated: Dec 21, 2025

Determining 3D Flow Fields via Multi-camera Light Field Imaging
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Accelerating Monte Carlo modeling of structured-light-based diffuse optical imaging via "photon sharing".

Shijie Yan, Ruoyang Yao, Xavier Intes

    Optics Letters
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    A new "photon sharing" Monte Carlo (MC) method accelerates light transport modeling for spatially modulated imaging. This efficient algorithm significantly speeds up simulations and inverse problem solving in complex 3D domains.

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    Area of Science:

    • Computational imaging
    • Optical physics
    • Scientific computing

    Background:

    • Spatially modulated imaging and single-pixel detection are increasingly used.
    • Accurate light transport modeling is computationally demanding for these techniques.
    • Existing methods lack efficiency for complex 3D simulations.

    Purpose of the Study:

    • To develop a computationally efficient Monte Carlo (MC) method for light transport modeling.
    • To accurately simulate spatially modulated illumination and detection patterns in 3D.
    • To accelerate the solving of inverse problems in spatially modulated imaging.

    Main Methods:

    • Implementation of an accelerated Monte Carlo (MC) algorithm named "photon sharing".
    • Simultaneous simulation of spatially modulated illumination and detection patterns.
    • Application in open-source MC simulators for mesh- and voxel-based benchmarks.

    Main Results:

    • Achieved 13.6x speedup in mesh-based MC benchmarks.
    • Achieved 5.5x speedup in voxel-based MC benchmarks.
    • Demonstrated a 12.4-fold speed improvement in solving inverse problems by concurrent Jacobian building.

    Conclusions:

    • The "photon sharing" MC method offers significant computational efficiency.
    • The algorithm accurately models light transport for spatially modulated imaging.
    • This method accelerates both forward and inverse problems in advanced imaging systems.