Image Dehazing Based on Haziness Analysis

被引:13
|
作者
Fan Guo [1 ,2 ]
Jin Tang [1 ]
Zi-Xing Cai [1 ]
机构
[1] School of Information Science and Engineering,Central South University
[2] Hunan Engineering Laboratory for Advanced Control and Intelligent Automation
基金
中国国家自然科学基金;
关键词
Image dehazing; haziness analysis; retinex theory; veil layer; haze image model; haze transmission;
D O I
暂无
中图分类号
TP391.41 [];
学科分类号
080203 ;
摘要
We present two haze removal algorithms for single image based on haziness analysis.One algorithm regards haze as the veil layer,and the other takes haze as the transmission.The former uses the illumination component image obtained by retinex algorithm and the depth information of the original image to remove the veil layer.The latter employs guided filter to obtain the refined haze transmission and separates it from the original image.The main advantages of the proposed methods are that no user interaction is needed and the computing speed is relatively fast.A comparative study and quantitative evaluation with some main existing algorithms demonstrate that similar even better quality results can be obtained by the proposed methods.On the top of haze removal,several applications of the haze transmission including image refocusing,haze simulation,relighting and 2-dimensional(2D)to 3-dimensional(3D) stereoscopic conversion are also implemented.
引用
收藏
页码:78 / 86
页数:9
相关论文
共 50 条
  • [21] Image Dehazing Based on Haze Degree Classification
    Zhao, Xing
    Zhang, Ting
    Chen, Wenxin
    Wu, Wei
    2020 CHINESE AUTOMATION CONGRESS (CAC 2020), 2020, : 4186 - 4191
  • [22] Single image dehazing based on fusion strategy
    Guo, Fan
    Zhao, Xin
    Tang, Jin
    Peng, Hui
    Liu, Lijue
    Zou, Beiji
    NEUROCOMPUTING, 2020, 378 : 9 - 23
  • [23] Research of Image Dehazing Algorithm Based on CNN
    Xu, Jin
    Zhu, Yaling
    Wang, Jundi
    Li, Xiangwei
    Zheng, Gang
    Zhou, Xiuyuan
    PROCEEDINGS OF 2024 INTERNATIONAL CONFERENCE ON MACHINE INTELLIGENCE AND DIGITAL APPLICATIONS, MIDA2024, 2024, : 426 - 431
  • [24] Single image dehazing based on Bayesian framework
    Wang, Duochao
    Wang, Yongguo
    Dong, Xuemei
    Hu, Xiyuan
    Peng, Silong
    Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics, 2010, 22 (10): : 1756 - 1761
  • [25] Image Dehazing Method Based on Diffusion Model
    Guan, Fengxu
    Lai, Haitao
    Zang, Hanyu
    Huang, Jinbao
    2024 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION, ICMA 2024, 2024, : 477 - 484
  • [26] Variational optimization based single image dehazing
    Singh, Kavinder
    Parihar, Anil Singh
    JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2021, 79
  • [27] Image Dehazing Based on Generative Adversarial Network
    Huang S.
    Wang B.
    Li H.
    Yang Y.
    Hu W.
    Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence, 2021, 34 (11): : 990 - 1003
  • [28] An image dehazing method based on scene segmentation
    Alharbi, Ebtesam Mohameed
    Shan, Yilin
    Ge, Peng
    Wang, Hong
    PROCEEDINGS OF THE 2016 4TH INTERNATIONAL CONFERENCE ON ADVANCED MATERIALS AND INFORMATION TECHNOLOGY PROCESSING (AMITP 2016), 2016, 60 : 162 - 166
  • [29] Single image dehazing based on vector quantization
    Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan
    Int J Comput Appl, 3-4 (83-93):
  • [30] An Image Dehazing Method Based on Atmospheric Veil
    Li, Shifeng
    Zhang, Dengyin
    Ju, Mingye
    PROCEEDINGS OF THE 2016 INTERNATIONAL FORUM ON MECHANICAL, CONTROL AND AUTOMATION (IFMCA 2016), 2017, 113 : 595 - 600