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    This study introduces a novel Visible-Near-Infrared (NIR) fusion method using top-hat transform to enhance outdoor image quality. The technique effectively preserves image details and color fidelity, addressing limitations of current fusion approaches.

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    Area of Science:

    • Computer Vision
    • Image Processing
    • Optics

    Background:

    • Outdoor color images suffer quality degradation from adverse weather, causing loss of contrast and detail due to light scattering.
    • Existing Visible-Near-Infrared (NIR) fusion methods improve image enhancement but struggle with edge preservation and color oversaturation.

    Purpose of the Study:

    • To propose a selective Visible-NIR fusion method for enhancing image quality by preserving relevant structures.
    • To address the limitations of current fusion techniques, specifically edge preservation and color oversaturation.

    Main Methods:

    • A novel method employing top-hat transform for selective fusion of Visible and NIR image structures is presented.
    • The technique focuses on merging the most relevant image information to improve detail and contrast.
    • Performance evaluation involved quantifying added image information and color changes.

    Main Results:

    • The proposed method demonstrates superior edge preservation compared to existing techniques.
    • Experimental results show high fidelity in maintaining the original image color.
    • Image quality improvements were robust across different color spaces.

    Conclusions:

    • The selective Visible-NIR fusion method effectively enhances image quality by preserving details and color.
    • This approach offers a significant improvement over current methods for degraded outdoor images.
    • The technique's robustness to color space variations makes it a versatile solution for image enhancement.