吉林大学学报(理学版)

• 计算机科学 • 上一篇    下一篇

基于滤波的单幅图像去雾方法

王永虎, 管庆吉, 李劲松, 齐妙   

  1. 东北师范大学 计算机科学与信息技术学院, 长春 130117
  • 收稿日期:2013-11-22 出版日期:2014-05-26 发布日期:2014-08-27
  • 通讯作者: 齐妙 E-mail:qim801@nenu.edu.cn

Single Image Dehazing Method Based on Filters

WANG Yonghu, GUAN Qingji, LI Jinsong, QI Miao   

  1. School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China
  • Received:2013-11-22 Online:2014-05-26 Published:2014-08-27
  • Contact: QI Miao E-mail:qim801@nenu.edu.cn

摘要:

基于Tarel方法提出一种新的基于滤波的单幅图像去雾方法. 先利用双边滤波求出初始的大气散射光, 较好地保持了边缘平滑纹理; 再利用自适应中值滤波器进一步求得边缘清晰、 纹理平滑、 景深信息真实的大气散射光; 然后基于分层搜索的四叉树分解方法求得大气光; 最后, 依据雾天退化模型得到复原的图像. 与经典去雾算法对比结果表明, 使用该方法复原的图像更接近真实图像, 特别对于纹理较丰富的区域和远景区域去雾效果更明显.

关键词: 图像去雾, 双边滤波, 自适应中值滤波, 四叉树分解

Abstract:

This paper introduces a novel single image dehazing method based on filters. Firstly, in order to maintain a good edge smooth texture, the initial atmospheric scattering light is estimated via bilateral filtering. Then, the initial atmospheric scattering light is refined via the adaptive median filter to keep sharp edges, smooth texture, and actual depth information. Next, the atmospheric light is obtained by the hierarchical searching method of quadtree subdivision. Finally, the dehazed image is restored by solving the atmosphere attenuation model. Compared with the results obtained by several existing classical dehazing methods, the experimental results show that the dehazed image by our proposed method is closer to the real scene image. Especially, it exhibits obvious superiority in dehazing regions with rich texture and distant scene.

Key words: image dehazing, bilateral filtering, adaptive median filter, quadtree subdivision

中图分类号: 

  • TP391.4