测试科学与仪器2021，Vol.12Issue(1)：53-60,8.DOI:10.3969/j.issn.1674-8042.2021.01.007
结合高斯混合模型的改进暗通道图像去雾方法
Improved dark channel image dehazing method based on Gaussian mixture model
摘要
Abstract
To solve the problem of color distortion after dehazing in the sky region by using the classical dark channel prior method to process the hazy images with large regions of sky,an improved dark channel image dehazing method based on Gaussian mixture model is proposed.Firstly,we use the Gaussian mixture model to model the hazy image,and then use the expectation maximization (EM)algorithm to optimize the parameters,so that the hazy image can be divided into the sky region and the non-sky region.Secondly,the sky region is divided into a light haze region,a medium haze region and a heavy haze region according to the different dark channel values to estimate the transmission respectively.Thirdly,the restored image is obtained by combining the atmospheric scattering model.Finally,adaptive local tone mapping for high dynamic range images is used to adjust the brightness of the restored image.The experimental results show that the proposed method can effectively eliminate the color distortion in the sky region,and the restored image is clearer and has better visual effect.关键词
图像处理/图像去雾/高斯混合模型/期望最大化算法/暗通道理论Key words
image processing/image dehazing/Gaussian mixture model/expectation maximization (EM)algorithm/dark channel theory引用本文复制引用
郭红光,陈永..结合高斯混合模型的改进暗通道图像去雾方法[J].测试科学与仪器,2021,12(1):53-60,8.基金项目
National Natural Science Foundation of China(Nos.61841303,61963023) （Nos.61841303,61963023）
Project of Humanities and Social Sciences of Ministry of Education in China(No.19YJC760012) （No.19YJC760012）
