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    This study introduces an improved line segment detector (LSD) for faster and more accurate infrared horizon detection in sea-sky scenes. The novel method enhances stability and significantly reduces processing time for sea surface monitoring.

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    Area of Science:

    • Remote Sensing
    • Image Processing
    • Oceanography

    Background:

    • Infrared imaging is crucial for sea surface monitoring.
    • Accurate horizon detection is essential for subsequent target analysis in sea-sky scenes.
    • Current methods face challenges in balancing processing speed and detection accuracy.

    Purpose of the Study:

    • To develop a novel, efficient, and accurate infrared horizon detection method.
    • To reduce the processing time for horizon detection in sea-sky infrared images.
    • To improve the stability and reliability of horizon detection.

    Main Methods:

    • Utilized a line segment detector (LSD) algorithm enhanced with gradient direction filtering.
    • Implemented rough sea-sky region extraction to optimize processing.
    • Employed random sample consensus for stitching detected horizon line segments.

    Main Results:

    • Achieved high detection accuracy in comparative experiments.
    • Demonstrated a significant reduction in processing time compared to existing methods.
    • Confirmed good performance regarding detection stability.

    Conclusions:

    • The proposed method offers a substantial improvement in infrared horizon detection efficiency and accuracy.
    • The gradient direction filtering and LSD combination effectively identifies horizon lines.
    • This approach is well-suited for real-time sea surface monitoring applications.