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Frequency and Spatial Dual Guidance for Image Dehazing

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Computer Vision – ECCV 2022 (ECCV 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13679))

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Abstract

In this paper, we propose a novel image dehazing framework with frequency and spatial dual guidance. In contrast to most existing deep learning-based image dehazing methods that primarily exploit the spatial information and neglect the distinguished frequency information, we introduce a new perspective to address image dehazing by jointly exploring the information in the frequency and spatial domains. To implement frequency and spatial dual guidance, we delicately develop two core designs: amplitude guided phase module in the frequency domain and global guided local module in the spatial domain. Specifically, the former processes the global frequency information via deep Fourier transform and reconstructs the phase spectrum under the guidance of the amplitude spectrum, while the latter integrates the above global frequency information to facilitate the local feature learning in the spatial domain. Extensive experiments on synthetic and real-world datasets demonstrate that our method outperforms the state-of-the-art approaches both visually and quantitatively. Our code is released publicly at https://github.com/yuhuUSTC/FSDGN.

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Acknowledgements

This work was supported by the JKW Research Funds under Grant 20-163-14-LZ-001-004-01 and the University Synergy Innovation Program of Anhui Province under Grant GXXT-2019-025. We acknowledge the support of GPU cluster built by MCC Lab of Information Science and Technology Institution, USTC. We also thank the technical support from Jie Huang.

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Authors and Affiliations

  1. University of Science and Technology of China, Hefei, China

    Hu Yu, Naishan Zheng, Man Zhou, Jie Huang, Zeyu Xiao & Feng Zhao

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  1. Hu Yu
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  2. Naishan Zheng
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  3. Man Zhou
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  4. Jie Huang
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  5. Zeyu Xiao
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  6. Feng Zhao
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Correspondence to Feng Zhao .

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Editors and Affiliations

  1. Tel Aviv University, Tel Aviv, Israel

    Shai Avidan

  2. University College London, London, UK

    Gabriel Brostow

  3. Google AI, Accra, Ghana

    Moustapha Cissé

  4. University of Catania, Catania, Italy

    Giovanni Maria Farinella

  5. Facebook (United States), Menlo Park, CA, USA

    Tal Hassner

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Yu, H., Zheng, N., Zhou, M., Huang, J., Xiao, Z., Zhao, F. (2022). Frequency and Spatial Dual Guidance for Image Dehazing. In: Avidan, S., Brostow, G., Cissé, M., Farinella, G.M., Hassner, T. (eds) Computer Vision – ECCV 2022. ECCV 2022. Lecture Notes in Computer Science, vol 13679. Springer, Cham. https://doi.org/10.1007/978-3-031-19800-7_11

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  • DOI: https://doi.org/10.1007/978-3-031-19800-7_11

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