Advanced Search
中文
Volume 43 Issue 8
Aug.  2021
Turn off MathJax
Article Contents
Abstract
References
Related Articles
ZHANG Jingyang, YAN Limin, CHEN Zhiheng. Nighttime Fog Removal Using the Dark Point Light Source Model[J]. Infrared Technology , 2021, 43(8): 798-803.
Citation: ZHANG Jingyang, YAN Limin, CHEN Zhiheng. Nighttime Fog Removal Using the Dark Point Light Source Model[J]. Infrared Technology , 2021, 43(8): 798-803.
shu

Nighttime Fog Removal Using the Dark Point Light Source Model

  • Microelectronics R & D Center, Shanghai University, Shanghai 200444, China

More Information
  • Received Date: November 23, 2020
  • Revised Date: December 24, 2020
    Graphical Abstract
    • Abstract
  • To address image distortion, texture loss, and low brightness in nighttime fog scenes, this paper proposes a nighttime defogging algorithm based on a dark point light source model. The dark point light source model was first constructed and the degraded image was processed by an algorithm that utilizes both bilateral filtering and limited contrast adaptive histogram equalization. Then, the defogging image was obtained by combining with the atmospheric scattering model. The experimental results show that this algorithm has a fast processing speed, a better effect of nighttime fogging, and a certain degree of improvement in terms of contrast, average gradient, and information entropy when compared with the contrast algorithm. This model can therefore effectively address image distortion, texture loss, and low brightness of fogging images.
    • FullText(HTML)
    • References (9)
  • [1]
    余顺园, 朱虹. 夜间有雾图像的光照模型构建及去雾[J]. 光学精密工程, 2017, 25(3): 729-734. https://www.cnki.com.cn/Article/CJFDTOTAL-GXJM201703025.htm

    YU S Y, ZHU H, Illumination model construction and defogging of night foggy image[J]. Optics And Precision Engineering, 2017, 25(3): 729-734. https://www.cnki.com.cn/Article/CJFDTOTAL-GXJM201703025.htm
    [2]
    郭璠, 邹北骥, 唐琎. 基于多光源模型的夜晚雾天图像去雾算法[J]. 电子学报, 2017, 45(9): 2127-2134. DOI: 10.3969/j.issn.0372-2112.2017.09.011

    GUO P, ZOU B J, TANG J. Defogging algorithm of night fog image based on multi light source model[J]. Acta Electronica Sinica, 2017, 45(9): 2127-2134. DOI: 10.3969/j.issn.0372-2112.2017.09.011
    [3]
    左健宏, 蔺素珍, 禄晓飞, 等. 基于雾线暗原色先验的红外图像去雾算法[J]. 红外技术, 2020, 42(6): 552-558. http://hwjs.nvir.cn/article/id/hwjs202006007

    ZUO J H, LIN S Z, LU X F, et al. Infrared image defogging algorithm based on fog line dark primary color prior[J]. Infrared Technology, 2020, 42(6): 552-558. http://hwjs.nvir.cn/article/id/hwjs202006007
    [4]
    ZHANG J, CAO Y, FANG S, et al. Fast haze removal for nighttime image using maximum reflectance prior[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017: 7418-7426.
    [5]
    LI Y, TAN R T, Brown M S. Nighttime haze removal with glow and multiple light colors[C]//Proceedings of the IEEE International Conference on Computer Vision, 2015: 226-234.
    [6]
    YU T, SONG K, MIAO P, et al. Nighttime Single Image Dehazing via Pixel-Wise Alpha Blending[J]. IEEE Access, 2019(7): 114619-114630. http://ieeexplore.ieee.org/document/8805086
    [7]
    HE K, SUN J, TANG X. Single image haze removal using dark channel prior[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 33(12): 2341-2353.
    [8]
    刘志成, 王殿伟, 刘颖, 等. 基于二维伽马函数的光照不均匀图像自适应校正算法[J]. 北京理工大学学报, 2016, 36(2): 191-196, 214. https://www.cnki.com.cn/Article/CJFDTOTAL-BJLG201602016.htm

    LIU Z C, WANG D W, LIU Y, et al. Adaptive correction algorithm for uneven illumination image based on two dimensional gamma function[J]. Journal of Beijing University of Technology, 2016, 36(2): 191-196, 214. https://www.cnki.com.cn/Article/CJFDTOTAL-BJLG201602016.htm
    [9]
    陈志恒, 严利民, 陆斌. 一种快速高效的实时视频去雾算法[J/OL]. 激光与光电子学进展: 1-12. [2020-11-24]. http://kns.cnki.net/kcms/detail/31.1690.TN.20191217.1447.008.html.

    CHEN Z H, YAN L M, LU B. A fast and efficient real time video defogging algorithm[J/OL]. Laser & Optoelectronics Progress: 1-12. [2020-11-24]. http://kns.cnki.net/kcms/detail/31.1690.TN.20191217.1447.008.html.
    • Related Articles

  • Related Articles

    [1]LI Jianghui. A Method and System for Infrared Image Simulation Based on ModelSim[J]. Infrared Technology , 2024, 46(7): 802-806.
    [2]WANG Xia, ZHAO Jiabi, SUN Qiyang, JIN Weiqi. Performance Evaluation Model for Infrared Polarization Imaging System[J]. Infrared Technology , 2023, 45(5): 437-445.
    [3]KONG Derui, XIA Ming, LI Haiying, CHEN Jun, ZHAO Peng. Theoretical Analysis and Matlab Simulation of Dynamic Vibration Absorber for Single-Piston Linear Compressor[J]. Infrared Technology , 2021, 43(10): 1014-1021.
    [4]ZHANG Jingyang, YAN Limin, CHEN Zhiheng. Nighttime Fog Removal Using the Dark Point Light Source Model[J]. Infrared Technology , 2021, 43(8): 798-803.
    [5]HU Yang, CHEN Cheng, HUA Sangtun, QIU Yafeng. Thermal Calculation of Countercurrent Cooling Tower and Design of Infrared Thermal Image Temperature Control System[J]. Infrared Technology , 2021, 43(3): 225-229.
    [6]PAN Hao, MA Yi, ZHOU Fangrong, MA Yutang, QIAN Guochao, WEN Gang. Research on the Theoretical Model Between Solar-blind UV and Atmospheric Temperature during Atmospheric Transmission[J]. Infrared Technology , 2020, 42(10): 1007-1012.
    [7]HAN Kun, YAO Ze, QIAO Kai, YANG Shuning, HE Yingping. Theoretical Model of Dynamic MTF of Low-Light-Level ICCD[J]. Infrared Technology , 2020, 42(3): 294-299.
    [8]SUN Jianning, SI Shuguang, WANG Xingchao, JIN Muchun, LI Dong, REN Ling, HOU Wei, ZHAO Min, GU Ying, QIAO Fangjian, ZHANG Haoda, CAO Yiqi. Preparation Method of K2CsSb Photocathode Using the Reflectance Theory Model[J]. Infrared Technology , 2017, 39(12): 1087-1091.
    [9]ZHANG Yao-jun, WU Gui-ling, LI Lei. Fusion for Infrared and Visible Light Images Based on Shearlet Transform and Quantum Theory Model[J]. Infrared Technology , 2015, (5): 418-423.
    [10]Theoretic Module of Uncooled IR Detector Performance Improvement[J]. Infrared Technology , 2002, 24(4): 31-34. DOI: 10.3969/j.issn.1001-8891.2002.04.009

  • Cited by

    Periodical cited type(1)

    1. 邱祥彪，杨晓明，孙建宁，王健，丛晓庆，金戈，曾进能，张正君，潘凯，陈晓倩. 高空间分辨微通道板现状及发展. 红外技术. 2024(04): 460-466 . 本站查看

    Other cited types(0)

Catalog

    Get Citation
    PDF
    XML
    Article views (294) PDF downloads (50) Cited by(1)
    Related

    Copyright © 《Infrared Technology》Editorial Office京ICP备000000000号-1

    Supported by: Beijing Renhe Information Technology Co., Ltd.  Baidu Analytics

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return