research-article

SADnet: Semi-supervised Single Image Dehazing Method Based on an Attention Mechanism

Authors:

Caiming ZhangAuthors Info & Claims

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 18, Issue 2

Article No.: 58, Pages 1 - 23

https://doi.org/10.1145/3478457

Published: 16 February 2022 Publication History

Abstract

Many real-life tasks such as military reconnaissance and traffic monitoring require high-quality images. However, images acquired in foggy or hazy weather pose obstacles to the implementation of these real-life tasks; consequently, image dehazing is an important research problem. To meet the requirements of practical applications, a single image dehazing algorithm has to be able to effectively process real-world hazy images with high computational efficiency. In this article, we present a fast and robust semi-supervised dehazing algorithm named SADnet for practical applications. SADnet utilizes both synthetic datasets and natural hazy images for training, so it has good generalizability for real-world hazy images. Furthermore, considering the uneven distribution of haze in the atmospheric environment, a Channel-Spatial Self-Attention (CSSA) mechanism is presented to enhance the representational power of the proposed SADnet. Extensive experimental results demonstrate that the presented approach achieves good dehazing performances and competitive running times compared with other state-of-the-art image dehazing algorithms.

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Haouassi SWu D(2024)An Efficient Attentional Image Dehazing Deep Network Using Two Color Space (ADMC2-net)Sensors10.3390/s2402068724:2(687)Online publication date: 22-Jan-2024
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Index Terms

SADnet: Semi-supervised Single Image Dehazing Method Based on an Attention Mechanism
1. Computer systems organization
  1. Architectures
    1. Other architectures
      1. Neural networks
2. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision representations
        Image representations
  2. Computer graphics
    1. Image manipulation
      1. Image processing

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cover image ACM Transactions on Multimedia Computing, Communications, and Applications

ACM Transactions on Multimedia Computing, Communications, and Applications Volume 18, Issue 2

May 2022

494 pages

ISSN:1551-6857

EISSN:1551-6865

DOI:10.1145/3505207

Editor:
Alberto Del Bimbo
University of Firenze, Italy

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Publication History

Published: 16 February 2022

Accepted: 01 July 2021

Revised: 01 June 2021

Received: 01 December 2020

Published in TOMM Volume 18, Issue 2

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National Natural Science Foundation of China
Natural Science Foundation of Shandong Province
Primary Research and Development Plan of Shandong Province
Fostering Project of Dominant Discipline and Talent Team of Shandong Province Higher Education Institutions

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Cited By

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徐航(2024)Semi-Supervised Image Dehazing Network Based on Deep LearningComputer Science and Application10.12677/csa.2024.14408914:04(193-200)Online publication date: 2024
https://doi.org/10.12677/csa.2024.144089
Zhang YCai YYan DLin R(2024)Real-world Scene Image Enhancement with Contrastive Domain Adaptation LearningACM Transactions on Multimedia Computing, Communications, and Applications10.1145/3694973Online publication date: 6-Sep-2024
https://doi.org/10.1145/3694973
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Li CRen YTong SSiam SZhang MWang JLiu YCao ZOkoshi TKo JLiKamWa R(2024)ChirpTransformer: Versatile LoRa Encoding for Low-power Wide-area IoTProceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services10.1145/3643832.3661861(479-491)Online publication date: 3-Jun-2024
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Hsu WLin H(2024)Context-detail-aware United Network for Single Image DerainingACM Transactions on Multimedia Computing, Communications, and Applications10.1145/363940720:5(1-18)Online publication date: 22-Jan-2024
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Dwivedi PChakraborty S(2024)A comprehensive qualitative and quantitative survey on image dehazing based on deep neural networksNeurocomputing10.1016/j.neucom.2024.128582610(128582)Online publication date: Dec-2024
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Vishwakarma SAnuradha Punj D(2024)Combined Light and Dark Priors over Variational Auto-encoder (CLDP-VAE) for single image dehazingInternational Journal of Information Technology10.1007/s41870-024-02356-117:2(975-985)Online publication date: 22-Dec-2024
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