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Improved small moving target detection method in infrared sequences under a rotational background.

Zhang Tong, Cui Can, Fu Wen Xing

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    |November 22, 2018
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    This study presents an improved optical flow method for detecting small moving targets in infrared images with rotational backgrounds. The technique effectively compensates for background motion, significantly reducing false alarms and enhancing detection accuracy.

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    Area of Science:

    • Computer Vision
    • Image Processing
    • Infrared Imaging

    Background:

    • Infrared image sequences often contain rotational backgrounds and moving targets, complicating detection and increasing false alarm rates.
    • Accurate detection of small moving targets in such complex scenarios is a significant challenge.

    Purpose of the Study:

    • To propose an improved method for detecting small moving targets in infrared images with rotational backgrounds.
    • To estimate and compensate for rotational motion in the background to enhance target detection.

    Main Methods:

    • Utilized Shi-Tomasi corner points for image detection and sparse optical flow to represent background rotation.
    • Employed the least squares method to estimate the perspective model parameters for background rotation.
    • Reconstructed the background motion vector field and compensated for rotation.
    • Applied differential and morphological methods for small moving target detection.

    Main Results:

    • The proposed method accurately detects small moving targets even in the presence of violent background rotation.
    • Experimental results demonstrate a significant reduction in false alarm rates compared to traditional methods.

    Conclusions:

    • The developed optical flow-based method is effective for small moving target detection in challenging infrared imaging conditions.
    • This approach offers a viable strategy for target interception algorithms in infrared imaging seeker applications.