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    This study introduces a novel multi-scale correction method using Chebyshev polynomial surface fitting to mitigate thermal radiation effects in uncooled infrared imaging systems, improving target detection accuracy.

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    Area of Science:

    • Infrared Imaging Technology
    • Image Processing
    • Optical Engineering

    Background:

    • Uncooled infrared imaging systems suffer from thermal radiation effects impacting target detection, tracking, and recognition.
    • These effects stem from heat sources within the target or detection window.
    • Existing correction methods may face challenges with accuracy and computational efficiency.

    Purpose of the Study:

    • To propose a novel multi-scale correction method for thermal radiation effects in uncooled infrared imaging.
    • To enhance the accuracy and efficiency of thermal radiation bias field estimation and correction.
    • To improve the overall performance of target detection, tracking, and recognition in infrared systems.

    Main Methods:

    • A multi-scale correction method employing fast surface fitting with Chebyshev polynomials.
    • Introduction of high-precision Chebyshev polynomial surface fitting in the gradient domain as a regularization term.
    • Utilization of a multi-scale iterative strategy and vector representation for accelerated optimization and fitting.
    • Application of split Bregman optimization to decompose and solve the minimization problem.

    Main Results:

    • The proposed method effectively corrects thermal radiation effects in simulated and real infrared images.
    • Chebyshev polynomial surface fitting in the gradient domain overcomes ill-posed matrix problems and enhances accuracy.
    • Vector representation and multi-scale iteration significantly speed up the correction process.
    • Experimental results demonstrate superior performance compared to state-of-the-art correction techniques.

    Conclusions:

    • The developed multi-scale correction method offers a robust solution for thermal radiation effects in uncooled infrared imaging.
    • The integration of Chebyshev polynomial fitting and split Bregman optimization achieves high accuracy and efficiency.
    • This approach significantly enhances the reliability of target detection, tracking, and recognition in challenging infrared imaging scenarios.