基于转换域与自适应伽马校正的去雾算法  

A dehazing algorithm based on transform domain and adaptive gamma correction

作　　者：王蓉 杨燕[1] WANG Rong;YANG Yan(School of Electronic and Information Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China)

机构地区：[1]兰州交通大学电子与信息工程学院,甘肃兰州730070

出　　处：《计算机工程与科学》2022年第9期1630-1637,共8页Computer Engineering & Science

基　　金：国家自然科学基金(61561030);兰州交通大学教改项目(JG201928)。

摘　　要：针对暗通道先验算法中存在的光晕效应以及天空区域偏色等问题,提出一种基于转换域与自适应伽马校正的图像去雾算法。首先通过将大气散射模型转换至对数域,结合暗通道先验理论提出对数域正相关关系;再利用高斯函数拟合正相关,从而得到粗级透射率;然后将有雾图像转换至HSV色彩空间,提取亮度分量构造自适应伽马校正因子,对粗级透射率进行修正,并使用交叉双边滤波操作实现透射率的进一步优化;最后结合大气散射模型与改进的局部大气光,实现无雾图像的有效复原。仿真实验表明,与几种经典算法相比,该算法复原结果去雾彻底且细节丰富,具有较好的色彩保真度,更接近真实场景。Aiming at the problems of halo effect and color cast of sky area in dark channel prior algorithm,an image dehazing algorithm based on transform domain and adaptive gamma correction is proposed.By transforming atmospheric scattering model to logarithmic domain,combined with the dark channel prior theory,a positive correlation in logarithmic domain is proposed.Then the Gaussian function is used to fit positive correlation to obtain the coarse transmission.At the same time,the hazy image is converted to HSV color space,the brightness component is extracted to construct an adaptive gamma correction factor,the coarse transmission is corrected,and cross bilateral filtering operation is used to further optimize the transmission.Finally,the restoration of the haze-free image is realized by the atmospheric scattering model and the improved local atmospheric light.Experimental results show that the recovered image has rich details and thorough degree of dehazing in comparison to some classic algorithms.Moreover,it is closer to the real scene because of the better color fidelity.

关 键 词：图像去雾 暗通道先验 对数域 正相关 自适应校正 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]