基于亮通道和暗通道结合的图像去雾  

Image Defogging Based on Combination of Image Bright and Dark Channels

作　　者：卢辉斌[1] 赵燕芳 赵永杰 温淑焕[2] 马金荣 Lam Hak Keung 王洪斌[2] Lu Huibin;Zhao Yanfang;Zhao Yongjie;Wen Shuhuan;Ma Jinrong;Lain Hak Keung;Wang Hongbin(Key Lab of Information Transmission and Signal Processing of Hebei Province,School of Information Science and Engineering,Yanshan University,Qinhuangdao,Hebei 066004,China;Key Lab of Industrial Computer Control Engineering of Hebei Province,Yanshan University,Qinhuangdao,Hebei 066004,China;Department of Informatics,King＇s College London,Strand,London,WC2R 2LS,United Kingdom)

机构地区：[1]燕山大学信息科学与工程学院河北省信息传输与信号处理重点实验室,河北秦皇岛066004 [2]燕山大学河北省工业计算机控制工程重点实验室,河北秦皇岛066004 [3]Department of Informatics, King's College London,Strand,London,WC2R 2LS,United Kingdom

出　　处：《光学学报》2018年第11期225-232,共8页Acta Optica Sinica

基　　金：国家自然科学基金(61773333,61473248)

摘　　要：低照度环境下图片质量会下降。同时,悬浮在空气中的烟雾、粉尘等物质形成的雾、霾,会导致图像的细节模糊不清,对户外拍照和计算机视觉应用造成了极大的影响。因此,对退化图像进行去雾处理,提高图像质量,在图像处理和计算机视觉领域具有非常重要的应用价值。提出一种基于亮通道和暗通道结合的雾霾天气图像去雾算法。基于退化图像的物理模型,提出一种空气光散射模型,通过亮通道和暗通道的结合来估计大气光值和透射率。该算法可以解决有雾图像恢复时天空区域的颜色失真问题,恢复图像的细节和颜色,提高图像的视觉效果。仿真结果表明,本文算法优于多尺度Retinex图像去雾算法。The picture quality is declined in the low illumination environment. Meanwhile, the fog and haze formed by smoke, dust and other substances suspended in the air will cause blurred image details, which have a great impact on outdoor photography and computer vision. Therefore, it has important application value for image processing and computer vision by defogging degraded images to improve image quality. We propose an image defogging algorithm based on the combination of bright and dark channel in fog and haze weather. A model of the air light scattering is proposed based on the physical model of degraded image. Air light value and transmissivity are estimated by using the combination of light channel prior and dark channel prior. The algorithm can solve color distortion problem of sky area when fog-free image is restored, recover the image details and color, and improve the vision effect of the image. Evaluation parameters are used to compare the image quality. Simulation results show that the algorithm proposed in this paper is better than multi-scale Retinex image defogging algorithm.

关 键 词：机器视觉 图像去雾 亮通道和暗通道 多尺度RETINEX算法 透射率 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]