王志伟
兰州交通大学电子与信息工程学院 兰州 730070
基金项目:国家自然科学基金(61561030)，甘肃省财政厅基本科研业务费基金(214138)，兰州交通大学教改基金(160012)
详细信息
作者简介:杨燕：女，1972年生，博士，教授、硕士生导师，主要研究方向为数字图像处理、智能信息处理、语音信号处理
王志伟：男，1996年生，硕士生，主要研究方向为数字图像处理、计算机视觉
通讯作者:杨燕 yangyantd@mail.lzjtu.cn
中图分类号:TN911.73; TP391.41计量
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被引次数:0
出版历程
收稿日期:2019-05-22
修回日期:2019-10-29
网络出版日期:2019-11-12
刊出日期:2020-03-19
Adaptive Image Dehazing Algorithm Based on Mean Unequal Relation Optimization
Yan YANG,,Zhiwei WANG
School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
Funds:The National Natural Science Foundation of China (61561030), The Fundamental Research Funds for the Gansu Provincial Finance Department (214138), The Research Fund of Teaching Reform Project of Lanzhou Jiao Tong University (160012)
摘要
摘要:针对暗通道先验去雾算法的不足，如天空区域透射率估计过小和在景深突变处易发生光晕效应，该文提出一种新颖且高效的去雾算法。首先通过几何分析建立雾图对应无雾图像暗通道图的平面扇形模型，然后设定一种新型的高斯均值函数，对其标准差进行自适应处理，用以估计扇形模型的上下边界值，通过引入均值不等关系对两侧边界进行逼近，拟合出最优无雾图像暗通道图，进一步求得最佳透射率，同时也改进局部大气光的探索方法并复原出最终结果。实验表明，与其它一些经典算法相比较，所提算法能广泛适用于各类图像，去雾程度彻底且效果清晰自然，具有较低的时间复杂度，有利于实时处理。
关键词:图像复原/
去雾/
暗通道先验/
透射率/
大气散射模型
Abstract:In view of shortcomings of dark channel prior dehazing methods, such as transmission in sky areas is small and halo effects are prone to occur in the edges, this paper proposes a novel and efficient dehazing algorithm. Firstly, the fan-shaped model with dark channel map of haze-free image is established by geometric analysis. Then a new Gaussian mean function is set to estimate the boundary values of the model and its standard deviation is adaptive processing. Mean-value unequal relationship is also introduced to approximate the two-sided boundary, which is used to fit the most excellent dark channel map of haze-free, further obtains the best transmission. At the same time the local atmospheric light is improved to recover the final result. Experimental results show that the proposed method can be widely applied to all kinds of images compared with other classical algorithms. The degree of dehazing is thorough, final result is clear and natural. More importantly, it is favorable for real-time processing that has low time complexity.
Key words:Image restoration/
Dehazing/
Dark Channel Prior (DCP)/
Transmission/
Atmospheric scattering model
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