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Single Image De-Hazing Using Globally Guided Image Filtering.

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    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |September 15, 2017
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    A new globally guided image filtering (G-GIF) method preserves fine structures better than existing techniques. This global approach enhances image quality, particularly for single image haze removal applications.

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    Area of Science:

    • Computer Vision
    • Image Processing
    • Digital Signal Processing

    Background:

    • Existing local edge-preserving smoothing methods like guided image filtering (GIF) and weighted guided image filtering (WGIF) struggle to maintain fine image structures.
    • This limitation impacts the quality of processed images, especially in applications requiring high structural fidelity.

    Purpose of the Study:

    • To introduce a novel globally guided image filtering (G-GIF) technique designed to overcome the structural preservation limitations of local methods.
    • To evaluate the effectiveness of G-GIF in single image haze removal.

    Main Methods:

    • The proposed G-GIF integrates a global structure transfer filter and a global edge-preserving smoothing filter.
    • The G-GIF was applied to the task of single image haze removal.

    Main Results:

    • Experimental results demonstrate that G-GIF significantly improves the preservation of fine image structures compared to existing GIF methods.
    • Images processed using G-GIF exhibit enhanced sharpness and better structural detail retention.

    Conclusions:

    • The globally guided image filtering (G-GIF) method offers superior performance in preserving fine structures.
    • G-GIF is a promising technique for applications like single image haze removal, yielding sharper and more detailed results.