research-article

LHNet: A Low-cost Hybrid Network for Single Image Dehazing

Authors:

Song GuoAuthors Info & Claims

MM '23: Proceedings of the 31st ACM International Conference on Multimedia

Pages 7706 - 7717

https://doi.org/10.1145/3581783.3612594

Published: 27 October 2023 Publication History

Abstract

Single image dehazing is a challenging task that requires both local detail and global distribution, and can be applied to various scenarios. However, physics-based dehazing algorithms perform well only in specific settings, while CNN-based algorithms struggle with capturing global information, and ViT-based approaches suffer from inadequate representation of local details. The shortcomings of the above three types of methods lead to issues such as imbalanced colors and incoherent details in the predicted haze-free image. To address these challenges, we propose a new Low-cost Hybrid Network called LHNet. The key insight of LHNet is the effective hybrid of different features, which can achieve better information fusion in the form of feature awareness at the cost of few parameters. This fusion approach narrows the gap between different features and enables LHNet to autonomously choose the fusion granularity to maximize the utilization of prior, local and global information. Extensive experiments are performed on the mainstream dehazing datasets, and the results show that LHNet achieves state-of-the-art performance in single image dehazing. By adopting our fusion approach, a better dehazing effect can be achieved than with other dehazing algorithms with more parameters, even when only CNN and ViT are used. The code is available at https://github.com/SHYuanBest/LHNet.

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Cited By

Islam MRahim NAnwar SSaqib MBakshi SMuhammad KCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)HazeSpace2M: A Dataset for Haze Aware Single Image DehazingProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681382(9155-9164)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3681382
Wang XRen WChen XFan HTang YHan ZCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)Uni-YOLO: Vision-Language Model-Guided YOLO for Robust and Fast Universal Detection in the Open WorldProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681212(1991-2000)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3681212
Wang JDeng ZLin TLi WLing SLin JCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)Beyond Direct Relationships: Exploring Multi-Order Label Pair Dependencies for Knowledge DistillationProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681029(8527-8535)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3681029
Show More Cited By

Index Terms

LHNet: A Low-cost Hybrid Network for Single Image Dehazing
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Reconstruction

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cover image ACM Conferences

MM '23: Proceedings of the 31st ACM International Conference on Multimedia

October 2023

9913 pages

ISBN:9798400701085

DOI:10.1145/3581783

General Chairs:
Abdulmotaleb El Saddik
University of Ottawa, Canada & MBZUAI, UAE
,
Tao Mei
HiDream.ai, China
,
Rita Cucchiara
University of Modena and Reggio Emilia, Italy
,
Program Chairs:
Marco Bertini
University of Florence, Italy
,
Diana Patricia Tobon Vallejo
Unversidad de Medellin, Colombia
,
Pradeep K. Atrey
University at Albany, State University of New York, USA
,
M. Shamim Hossain
M. Shamim Hossain (King Saud University, KSA

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Published: 27 October 2023

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Research and Development Projects of National Key fields
National Natural Science Foundation of China for Key Program
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MM '23: The 31st ACM International Conference on Multimedia

October 29 - November 3, 2023

Ottawa ON, Canada

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Cited By

Islam MRahim NAnwar SSaqib MBakshi SMuhammad KCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)HazeSpace2M: A Dataset for Haze Aware Single Image DehazingProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681382(9155-9164)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3681382
Wang XRen WChen XFan HTang YHan ZCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)Uni-YOLO: Vision-Language Model-Guided YOLO for Robust and Fast Universal Detection in the Open WorldProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681212(1991-2000)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3681212
Wang JDeng ZLin TLi WLing SLin JCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)Beyond Direct Relationships: Exploring Multi-Order Label Pair Dependencies for Knowledge DistillationProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681029(8527-8535)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3681029
Yuan SChen JJiang WZhao ZGuo S(2024)LHNetV2: A Balanced Low-Cost Hybrid Network for Single Image DehazingIEEE Transactions on Multimedia10.1109/TMM.2024.337713326(8197-8209)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1109/TMM.2024.3377133
Feng YSu ZMa LLi XLiu RZhou F(2024)Bridging the Gap Between Haze Scenarios: A Unified Image Dehazing ModelIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2024.341467734:11(11070-11085)Online publication date: Nov-2024
https://doi.org/10.1109/TCSVT.2024.3414677

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