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Single Image Haze Removal Based on Global-Local Optimization for Depth Map

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Advances in Multimedia Information Processing – PCM 2017 (PCM 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10735))

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Abstract

With the wide application of computer vision system, image haze removal has become a new challenge. A great number of image dehazing methods are proposed, which have varying degrees of dehazing effects and different shortcomings. The color attenuation prior for image haze removal presents a new way based on depth map estimation. The novel method performs well with little distortion and natural colors. This paper discusses the color attenuation prior for image haze removal and proposes the haze removal method based on global-local optimization for depth map. Regarding the halo artifacts in dehazing images, we combine the minimum filter and minimum-maximum filter to detect the potential areas of the halo artifacts and suppress them. For the case of the underestimation of depth information, we take advantage of the atmospheric light estimation to perform global optimization for final depth map. Experimental results demonstrate excellent performance of the proposed method.

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Acknowledgements

This work was partially supported by the National Key Research and Development Program of China (Grant No. 2016YFC0801003), the National Natural Science Foundation of China (No. 61370121, No. 61421003).

Author information

Authors and Affiliations

  1. Beijing Key Laboratory of Digital Media, School of Computer Science and Engineering, Beihang University, Beijing, 100083, China

    Hongda Zhang, Yuanyuan Gao, Hai-Miao Hu, Qiang Guo & Yukun Cui

  2. State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, 100191, China

    Hai-Miao Hu

Authors
  1. Hongda Zhang
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  2. Yuanyuan Gao
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  3. Hai-Miao Hu
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  4. Qiang Guo
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  5. Yukun Cui
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Corresponding author

Correspondence to Hai-Miao Hu .

Editor information

Editors and Affiliations

  1. University of Electronic Science and Technology of China, Chengdu, China

    Bing Zeng

  2. University of Chinese Academy of Sciences, Beijing, China

    Qingming Huang

  3. University of Ottawa, Ottawa, Ontario, Canada

    Abdulmotaleb El Saddik

  4. University of Electronic Science and Technology of China, Chengdu, China

    Hongliang Li

  5. Chinese Academy of Sciences, Beijing, China

    Shuqiang Jiang

  6. Harbin Institute of Technology, Harbin, China

    Xiaopeng Fan

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Zhang, H., Gao, Y., Hu, HM., Guo, Q., Cui, Y. (2018). Single Image Haze Removal Based on Global-Local Optimization for Depth Map. In: Zeng, B., Huang, Q., El Saddik, A., Li, H., Jiang, S., Fan, X. (eds) Advances in Multimedia Information Processing – PCM 2017. PCM 2017. Lecture Notes in Computer Science(), vol 10735. Springer, Cham. https://doi.org/10.1007/978-3-319-77380-3_12

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  • DOI: https://doi.org/10.1007/978-3-319-77380-3_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-77379-7

  • Online ISBN: 978-3-319-77380-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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