摘要
为了解决去雾过程中图像边缘产生光带的情况和去雾之后图像整体变暗的现象,提出了一种新颖的基于优化后透射率和半逆法的图像去雾算法。首先,针对图像边缘处暗通道失效情况,运用透射率修正机制来消除边缘处的光带现象,从而提高暗通道先验的适用范围;其次,从大气散射模型出发,利用半逆算法得到大气整体光照值;最后,针对去雾之后整幅图片颜色变暗淡的现象,采用基于小波变换的图像对比度算法来进行增强处理,改善去雾图像的视觉效果。实验结果表明,该算法能够更有效地去雾,而且去雾能力优于原算法。
In order to solve the phenomenon of the edges of the image produce light bands in the de-hazing process and the whole image’s color becomes dim after de-hazing,this paper proposed a novel algorithm based on improved transmission and semi-inverse algorithm.Aiming at the dark channel prior failure at the edge of the image,a transmission correction mechanism is proposed in this paper to eliminate the band phenomenon at the edge and improve the application of the dark channel prior.Secondly,based on the atmospheric scattering model,the atmospheric light is obtained by using the semi-inverse algorithm.Then for the situation that the color of the whole image become dim after de-hazing,the image contrast algorithm based on wavelet transform is used to enhance the stretching treatment and improve the visual effect of image.The experimental results show that the algorithm can remove fog more effectively,and the ability to de-haze is better than the original algorithm.
作者
彭莉婷
李波
Peng Liting;Li Bo(Hubei Key Laboratory of Intelligent Information Processing & Real-time Industrial System,Wuhan University of Science & Technology,Wuhan 430065,China)
出处
《计算机应用研究》
CSCD
北大核心
2019年第10期3174-3178,共5页
Application Research of Computers
基金
国家自然科学基金资助项目(61572381,61273303)
关键词
暗通道先验
透射率
小波变换
半逆法
图像去雾
dark channel prior
transmission
wavelet transform
semi-inverse
image de-hazing
