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Fast Single Image Dehazing Using Saturation Based Transmission Map Estimation.

Se Eun Kim, Tae Hee Park, Il Kyu Eom

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |November 1, 2019
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    Summary

    This study introduces a fast and effective single image dehazing algorithm. It accurately removes atmospheric haze and color casts without needing training or prior data.

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    Area of Science:

    • Computer Vision
    • Image Processing

    Background:

    • Single image dehazing is an ill-posed problem.
    • Existing haze removal methods often require training or complex processing.

    Purpose of the Study:

    • To develop a simple, fast, and powerful algorithm for single image dehazing.
    • To address challenges in removing atmospheric haze and color casts.

    Main Methods:

    • Estimating medium transmission based on scene radiance saturation using a stretching method.
    • Applying a white balance technique for color veil removal.
    • Pixel-wise transmission estimation without patch constraints.

    Main Results:

    • The proposed algorithm achieves efficient and effective haze removal.
    • It outperforms state-of-the-art methods in computational complexity and dehazing efficiency.
    • The method successfully removes color casts caused by fine or yellow dust.

    Conclusions:

    • The novel dehazing algorithm is simple, fast, and requires no training or prior knowledge.
    • It offers a significant improvement over existing single image dehazing techniques.
    • The method is robust for various image conditions, including those with color casts.