基于区域对比度约束的暗通道图像去雾  

Image Dehazing of Dark Channels Based on Area Contrast Constraint

作　　者：王振东 靖旭[1] 孙国栋 程乙轮 喻璐璐 管雯璐 秦来安 谭逢富 张巳龙 何枫 侯再红 Wang Zhendong;Jing Xu;Sun Guodong;Cheng Yilun;Yu Lulu;Guan Wenlu;Qin Laian;Tan Fengfu;Zhang Silong;He Feng;Hou Zaihong(Key Laboratory of Atmospheric Optics ,Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei , Anhui 230031, China;University of Science and Technology of China , Hefei , Anhui 230026,China)

机构地区：[1]中国科学院安徽光学精密机械研究所大气光学重点实验室,安徽合肥230031 [2]中国科学技术大学,安徽合肥230026

出　　处：《中国激光》2019年第8期268-273,共6页Chinese Journal of Lasers

基　　金：国家自然科学基金(41405014)

摘　　要：为了保持图像明暗区域的对比度约束,提出了一种改进的暗通道去雾算法;该算法首先将原始图像分割成适当的明暗双区域,并计算相应的对比度比值,再使用基于中值滤波的暗通道去雾算法处理图像暗区域部分,最后利用亮度精确控制的双直方图均衡算法,以最大程度保持区域对比度不变为约束条件,修正图像较亮区域的亮度分布。结果表明:对比相关去雾算法,利用所提算法最终处理后的图像能够在信息熵值、平均梯度和亮度标准差等方面取得明显增益,进一步凸显图像中被雾霾环境所掩盖的细节特征。An improved dark channel dehazing algorithm is proposed to maintain the contrast constraints of the bright and dark areas of an image. According to this algorithm, the original image is first divided into light and dark two areas and the corresponding contrast ratio is calculated. Then, the dark channel dehazing algorithm based on median filtering is used to process the dark area of the image. Finally, the double histogram equalization algorithm with accurate brightness control is used to enhance the brighter area of the image with the constraint that the regional contrast constant is maximized. The results show that compared with that processed by the correlation dehazing algorithm, the final image processed by the proposed algorithm can be significantly improved in terms of information entropy, average gradient and standard deviation of brightness. The proposed algorithm can further highlight the details of the image covered by a hazy environment.

关 键 词：大气光学 图像增强 大气透过率 图像去雾 暗通道 

分 类 号：O435.1[机械工程—光学工程] TP391.4[理学—光学]