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Model Based Edge-Preserving and Guided Filter for Real-World Hazy Scenes Visibility Restoration

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Abstract

Transmission estimation is the most challenging part for single image haze removal and very sensitive to environment noise. However, most existing single image dehazing algorithms are far from satisfactory in terms of restoring an image’s details and noise removal. To address this issue, an improved haze imaging model with transmission refinement based on dark channel prior is constructed to preserve the edge details and enhance visibility. Then, a fast single image dehazing algorithm called TSGA algorithm is proposed for complex real-world images. A refined transmission map obtained by TGVSH regularity scheme provides more edges and finer details and is less susceptible to noise. Guided filter and adaptive histogram equalization greatly enhance the visibility and color contrast of the scenes and significantly improve the drawback of halo artifacts. A large quantity of comparative experiment results demonstrate that the proposed algorithm simultaneously removes the serious effect of haze and noise, effectively makes the restored images look more natural, and has a lower time complexity. All these make it a good candidate for image segmentation, object recognition, and target tracking in complex real-world weather conditions.

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Acknowledgements

This research is supported by National Natural Science Foundation of People’s Republic of China (Grant No. 91026005).

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Authors and Affiliations

  1. School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Zi-yang Wang, Jian Luo, Kai-yu Qin & Gun Li

  2. School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Hou-biao Li

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  1. Zi-yang Wang
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  2. Jian Luo
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  3. Kai-yu Qin
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  4. Hou-biao Li
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  5. Gun Li
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Correspondence to Gun Li.

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Funding

This study was funded by the National Natural Science Foundation of People’s Republic of China (Grant No. 91026005).

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Wang, Zy., Luo, J., Qin, Ky. et al. Model Based Edge-Preserving and Guided Filter for Real-World Hazy Scenes Visibility Restoration. Cogn Comput 9, 468–481 (2017). https://doi.org/10.1007/s12559-017-9458-4

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  • DOI: https://doi.org/10.1007/s12559-017-9458-4

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