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    Area of Science:

    • Optics and Photonics
    • Computational Imaging
    • Image Reconstruction

    Background:

    • Single-pixel imaging offers advantages in specific optical scenarios.
    • Computational ghost imaging typically requires dynamic pattern generation.
    • 3D imaging presents challenges in depth information acquisition.

    Purpose of the Study:

    • To propose a scanning single-pixel imaging method using binary random structured illumination.
    • To achieve 3D image reconstruction at arbitrary depths.
    • To enhance computational ghost imaging efficiency.

    Main Methods:

    • Utilizing a simple optical system with a binary spatial light modulator.
    • Employing computational propagation of binary random patterns for illumination.
    • Scanning a single binary random pattern for image acquisition.

    Main Results:

    • Successful 3D image reconstruction at various depths demonstrated via simulations and experiments.
    • Elimination of the need to regenerate patterns for each measurement.
    • Improved image quality observed with an increased number of pixels in the binary random pattern.

    Conclusions:

    • The proposed method offers an efficient approach to 3D single-pixel imaging.
    • Computational propagation of binary patterns enables flexible illumination.
    • Pattern complexity influences the quality of reconstructed images.