结合自适应融合和双边界光幕估计的图像去雾  

Image Dehazing Combining Adaptive Fusion and Dual-Boundary Estimation Light Veil

作　　者：牛学钰 杨燕[1] NIU Xueyu;YANG Yan(College of Electronic and Information Engineering,Lanzhou Jiaotong University,Lanzhou 730000,China)

机构地区：[1]兰州交通大学电子与信息工程学院,兰州730000

出　　处：《电光与控制》2024年第6期94-100,共7页Electronics Optics & Control

基　　金：甘肃省教育厅高等学校产业支撑计划(2021CYZC-04);甘肃省优秀研究生“创新之星”项目(2023CXZX-547)。

摘　　要：针对图像去雾算法存在的细节丢失、颜色失真、去雾不彻底等问题,提出一种利用通道估计光幕上下边界、自适应融合大气光的去雾算法。首先,根据有雾图像最小通道估计大气光幕上边界,以雾图B通道为主、RG通道差补偿结合线性变换得到大气光幕下边界,对上下边界进行逼近优化,经过小波变换融合两边界;其次,分别用RGB三通道的平均值和亮度中通道获取不同的粗糙大气光,以亮度均值为调节因子自适应融合;最后,结合去雾模型复原出无雾图像。实验结果表明,所提算法复原的图像去雾彻底、清晰自然、能保留较多图像细节,具有良好的有效性和鲁棒性。Aiming at the problems of detail loss,color distortion,and incomplete dehazing of image dehazing algorithms,this paper proposes a dehazing algorithm with channel estimation of the upper and lower boundaries of the light veil and adaptive fusion of atmospheric light.Firstly,the upper boundary of the atmospheric light veil is estimated according to the minimum channel of the foggy image,and the lower boundary of the atmospheric light veil is obtained based on B channel of the foggy image,RG channel difference compensation,and linear transformation.The upper and lower boundaries are optimized for approximation,and the two boundaries are fused by the wavelet transform.Secondly,the average value of the three channels of RGB and the middle channel of brightness are used to obtain different rough atmospheric light,and the average brightness value is used as the regulator for adaptive fusion.Finally,the haze-free image is recovered by using the haze removal model.The experimental results show that the images recovered by the proposed algorithm are thoroughly defogged,clear and natural,and can retain more image details with good effectiveness and robustness.

关 键 词：图像去雾 大气光幕 边界优化 小波变换 自适应融合 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]