Computer Engineering and Applications ›› 2016, Vol. 52 ›› Issue (7): 166-170.

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Regional adaptive image haze removal method based on dark channel prior

LIU Dongdong1, CHEN Ying2   

  1. Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education, Jiangnan University, Wuxi, Jiangsu 214000, China
  • Online:2016-04-01 Published:2016-04-19

基于暗原色先验的区域自适应图像去雾方法

刘冬冬1,陈  莹2   

  1. 江南大学 轻工过程先进控制教育部重点实验室,江苏 无锡 214000

Abstract: Images taken in foggy weather are seriously degraded due to the scattering of atmospheric particles. A simple and effective haze removal algorithm from a single image is proposed. Firstly, a halo evaluator is designed to detect halo zone. Then, precise transmission rat is obtained by weight fusion of single pixel based rate and block area based one, both taking the prior of dark channel. The weight is determined according to the halo evaluator. Finally, a parameter is added for image recovery to limit the low transmission and to protect the sky area. Experiments show that compared with other methods, more vivid and natural images can be recovered by the proposed method, especially at the edges of the foreground and the background and in the sky area.

Key words: dehazing, dark channel prior, weighting, transmission

摘要: 在雾霾天气条件下,由于大气粒子的散射作用导致拍摄的图像严重退化。针对这一问题,提出一种简单有效的单幅图像去雾算法。设计晕光估计算子检测出晕光区域,在暗原色先验条件下,根据晕光估计值获取区域自适应融合权值,进而在不同区域采用不同的加权方式融合基于单像素估算的透射率与基于块状区域的透射率以获取精确透射率,有效地消除了晕光效应;最后增加参数限制透射率过低,保护了天空区域。实验表明该算法复原的图像清晰自然,尤其是在前景与背景的边缘处及天空区域能够达到很好的去雾效果。

关键词: 去雾, 暗原色先验, 加权, 透射率