改进的基于雾气理论的视频去雾

刘海波; 杨杰; 吴正平; 张庆年; 邓勇

doi:10.3788/OPE.20162407.1789

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改进的基于雾气理论的视频去雾

信息科学 | 更新时间：2020-08-13

- 改进的基于雾气理论的视频去雾
- Improved video defogging based on fog theory
- 光学精密工程 2016年24卷第7期页码：1789-1798
- 作者机构：
  
  1.湖南工学院电气与信息工程学院, 湖南衡阳 421002
  2.武汉理工大学光纤传感与信号处理教育部重点实验室, 湖北武汉 430070
  3.武汉理工大学交通学院, 湖北武汉 430070
- 作者简介：
  
  刘海波(1981-), 男, 湖北武汉人, 博士, 副教授, 2011年于湖南大学获得硕士学位, 2015年于武汉理工大学获得博士学位, 主要从事图像处理及模式识别方面的研究。E-mail:seainlost81@126.com E-mail: seainlost81@126.com
  [ "杨杰(1960-), 女, 湖北武汉人, 博士, 教授, 1988年于武汉交通科技大学获得硕士学位, 1999年于上海交通大学获得博士学位, 2002年于韩国全北大学完成博士后学习, 主要从事信息处理、图像处理和人工智能等方面的研究。E-mail:jieyang509@163.com" ]
- 基金信息：
  
  国家自然科学基金资助项目(No.51479159);交通运输部软科学项目(No.2013-322-811-470);湖南省教育厅科学研究重点项目(No.15A046);湖南工学院大学生创新训练计划项目(No.H1519)
- DOI：10.3788/OPE.20162407.1789
  中图分类号： TP391.9;TN941.1
- 收稿日期：2015-11-20，
  
  录用日期：2016-1-11，
  
  纸质出版日期：2016-06
- 稿件说明：
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刘海波, 杨杰, 吴正平, 等. 改进的基于雾气理论的视频去雾[J]. 光学精密工程, 2016,24(7):1789-1798.

Hai-bo LIU, Jie YANG, Zheng-ping WU, et al. Improved video defogging based on fog theory[J]. Optics and precision engineering, 2016, 24(7): 1789-1798.
刘海波, 杨杰, 吴正平, 等. 改进的基于雾气理论的视频去雾[J]. 光学精密工程, 2016,24(7):1789-1798. DOI： 10.3788/OPE.20162407.1789.

Hai-bo LIU, Jie YANG, Zheng-ping WU, et al. Improved video defogging based on fog theory[J]. Optics and precision engineering, 2016, 24(7): 1789-1798. DOI： 10.3788/OPE.20162407.1789.

摘要

为了进一步提高有雾视频的可用性，提出了一种改进的基于雾气理论的视频去雾方法。该方法以雾气理论为基础，利用暗原色先验知识以及Retinex方法和图像融合的方式，将从视频背景图像求取的大气光值和介质传播图应用于视频的所有帧以便去除雾气。从主观定性评价、客观定量评价和运算速度3个方面对视频去雾效果进行了评价。结果表明，对分辨率为480×640的视频，本文方法的运算速度为5.45 frame/s，不仅获得了较快的处理速度且能有效避免复原视频中出现颜色跳变的现象。由于本文采用区间估计的方式对大气光值进行估计，同时利用图像复原和图像增强的方法求取介质传播图，因此，复原视频的清晰度和对比度比典型的视频去雾方法有所提高，颜色效果也比较好。

Abstract

To improve the usability of a foggy video

an improved video defogging method based on fog theory was proposed. By using dark channel prior knowledge

Retinex method and image fusion

the method applies the values of global atmospheric light and a medium transmission map estimated from the video backgrfound image to defogging of all the video frames. The effects of the defogging for the video image were evaluated by three methods in subjective qualitative evaluation

objective quantitative evaluation and operation speeds. Experimental results demonstrate that the proposed method runs at 5.45 frame/s for a video image of 480×640

and it not only obtains a fast processing speed but also effectively avoids color jump during the process of restoring image. As the modified method uses the interval estimation to estimate the value of global atmospheric light

and combinates image restoration and image enhancement to obtain the value of medium transmission map

it improves the visibility and contrast of restored video image effectively as well as color effect as compared with the traditional video defogging methods.

关键词

Keywords

references

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