Dehazing algorithm using adaptive dark channel fusion and sky compensation  

自适应暗通道融合和天空补偿的去雾算法

作　　者：LU Xinxuan YANG Yan 陆鑫璇;杨燕(兰州交通大学电子与信息工程学院,甘肃兰州730070)

机构地区：[1]School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China

出　　处：《Journal of Measurement Science and Instrumentation》2021年第2期177-187,共11页测试科学与仪器（英文版）

基　　金：National Natural Science Foundation of China(No.61561030);Natural Science Foundation of Science and Technology Department of Gansu Province(No.1310RJZA050);Basic Research Projects Supported by Operating Expenses of Finance Department of Gansu Province(No.214138)。

摘　　要：Aiming at the inaccurate transmission estimation problem of dark channel prior image dehazing algorithm in the sudden change area of depth of field and sky area,a dehazing algorithm using adaptive dark channel fusion and sky compensation is proposed.Firstly,according to the characteristics of minimum filtering of large window scale and small window scale in the dark channel prior,the fused dark channel is obtained by weighted fusion of the approximate depth of field relationship,thus obtaining the primary transmission.Secondly,use the down-sampling to optimize the primary transmission combined with gray scale image of haze image by fast joint bilateral filtering,then restore the original image size by up-sampling,and the compensation of the Gaussian function is used in the sky area to obtain corrected transmission.Finally,the improved atmospheric light is combined with atmospheric scattering model to recover haze-free image.Experimental results show that the algorithm can recover a large amount of detailed information of the image,obtain high visibility,and effectively eliminate the halo effect.At the same time,it has a better recovery effect on bright areas such as the sky area.

关 键 词：dark channel prior approximate depth of field weighted fusion fast joint bilateral filtering Gaussian function compensation 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]