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Scene-based nonuniformity correction for airborne point target detection systems.

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    Area of Science:

    • Optics and Photonics
    • Signal Processing
    • Aerospace Engineering

    Background:

    • Airborne infrared search and track (IRST) systems frequently encounter nonuniform noise in acquired images.
    • Nonuniformity in infrared focal-plane arrays (FPAs) degrades image quality and detection performance.
    • Accurate image correction is crucial for effective target detection and system reliability.

    Purpose of the Study:

    • To propose a novel scene-based nonuniformity correction method for IR FPA images.
    • To address the challenge of nonuniform noise in airborne IRST systems.
    • To develop a method suitable for real-time applications with low computational complexity.

    Main Methods:

    • A scene-based approach utilizing constant statistics of received radiation ratios between adjacent pixels.
    • Recursive computation of pixel gain based on median-estimated adjacent pixel ratios.
    • Establishment of a mathematical model for error propagation, considering random noise and recursive calculations.

    Main Results:

    • The proposed method effectively corrects nonuniform noise in IR FPA images.
    • Experimental results demonstrate compelling performance on various scenes using a long-wave Sofradir FPA.
    • The method maintains traditional calibration characteristics and temporal drift compensation.

    Conclusions:

    • The developed method offers a robust and computationally efficient solution for nonuniformity correction in airborne IRST systems.
    • Its suitability for real-time applications is confirmed by low complexity and simplicity of implementation.
    • The method provides a significant advancement in processing IR FPA imagery for enhanced target detection.