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Related Experiment Video

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Double filter iterative ghost imaging for high quality edge and image acquisition.

Cheng Zhou, Deli Feng, Gangcheng Wang

    Optics Express
    |July 21, 2023
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel double filter iterative ghost imaging method. It enhances image quality and reduces processing time, offering superior performance in complex imaging scenarios.

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    Area of Science:

    • Computational imaging
    • Image processing
    • Optical sensing

    Background:

    • Ghost imaging faces challenges in image quality and time efficiency for practical applications.
    • Iterative regularization and filtering techniques are crucial for enhancing image reconstruction.

    Purpose of the Study:

    • To develop an advanced ghost imaging method for high-quality image reconstruction with reduced measurements and iterations.
    • To combine iterative regularization with advanced filtering for improved de-noising and edge preservation.

    Main Methods:

    • A double filter iterative ghost imaging approach integrating projected Landweber iterative regularization.
    • Joint iteration with block matching 3D filtering and guided filtering for de-noising and edge preservation.

    Main Results:

    • Achieved 4-6 dB higher peak signal-to-noise ratio compared to existing methods for 'rice' and 'aircraft' targets.
    • Demonstrated superior edge detection accuracy and richness in experimental and simulation results.
    • Successfully reconstructed high-quality images and edge information with low measurements and iterations.

    Conclusions:

    • The proposed double filter iterative ghost imaging method significantly improves imaging quality and efficiency.
    • This technique is valuable for applications requiring simultaneous imaging and edge detection, such as intelligent driving and remote sensing.