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Single image dehazing using second-generation wavelet transforms and the mean vector L2-norm

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Abstract

Single image dehazing remains a seminal area of study in computer vision. Despite the huge number of studies that have addressed haze in a single image, the restoration images have not yet reached a satisfactory level in terms of visual appearance and time complexity burden. In this paper, a novel single image haze removal technique based on edge and fine texture preserving is introduced. To achieve better visual quality from the hazy image, the proposed technique uses mean vector L2-norm that is core of window sampling to estimate the transmission map. Then, second-generation wavelet transform filter is utilized in order to enhance the estimated transmission map of the resulted image. The usage of second-generation wavelet filter in this paper is due to its effectiveness while achieving fast speed. Experimental outcomes present that the proposed technique achieves competitive achievements in comparison with up-to-date state-of-the-art image dehazing methods in both quantitative and qualitative assessments, i.e., visual effects, universality, and computational processing speed.

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Acknowledgements

The authors would like to thank the anonymous reviewers for their constructive comments to improve the quality of this paper.

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Authors and Affiliations

  1. Faculty of Engineering, University of Zawia, Zawiya, Libya

    Asem Khmag

  2. Faculty of Engineering, Universiti Putra Malaysia (UPM), Selangor, Malaysia

    S. A. R. Al-Haddad, Abd Rahman Ramli & Bahareh Kalantar

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  1. Asem Khmag
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  2. S. A. R. Al-Haddad
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  3. Abd Rahman Ramli
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  4. Bahareh Kalantar
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Correspondence to Asem Khmag.

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Khmag, A., Al-Haddad, S.A.R., Ramli, A.R. et al. Single image dehazing using second-generation wavelet transforms and the mean vector L2-norm. Vis Comput 34, 675–688 (2018). https://doi.org/10.1007/s00371-017-1406-5

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