基于暗通道先验的去雾算法研究  

Research of Dehazing Algorithm Based on Dark Channel Prior

作　　者：蒲亨飞 李震 李良荣 Pu Hengfei;Li Zhen;Li Liangrong(College of Big Data and Information Engineering,Guizhou University,Guiyang,Guizhou 550025,China)

机构地区：[1]贵州大学大数据与信息工程学院,贵州贵阳550025

出　　处：《激光与光电子学进展》2021年第20期167-173,共7页Laser & Optoelectronics Progress

基　　金：国家自然科学基金(61361012)。

摘　　要：针对暗通道先验去雾算法中存在的块效应、算法复杂度高等问题,提出了一种改进的基于暗通道先验的去雾算法。首先,通过暗通道先验去雾算法得到粗略透射率,再通过峰值信噪比自适应调节雾气参数,以获取最优透射率。然后,将上述结果分别作为多层感知器的输入向量和目标向量进行训练,以建立粗略透射率到最优透射率之间的映射并得到最优透射率。最后,结合大气光值复原无雾图像。实验结果表明,本算法能有效改善块效应,提高复原效率,且能在一定程度上提升图像细节的清晰度。Aiming at the problems of block effect and high algorithm complexity in the dark channel prior dehazing algorithm,we propose an improved dehazing algorithm based on the dark channel prior.First,row transmittance is obtained through the dark channel prior dehazing algorithm,and then the haze parameters are adjusted adaptively by the peak signal-to-noise ratio to obtain the optimized transmittance.Then,the above results are trained as the input vector and the target vector of the multilayer perceptron to establish the mapping between the row transmittance and the optimized transmittance and obtain the optimized transmittance.Finally,the image is restored by the atmosphere light value to obtain the haze-free image.Experimental results show that the algorithm can effectively improve the block effect,improve the restoration efficiency,and improve the clarity of image details to a certain extent.

关 键 词：图像处理 暗通道先验 多层感知器 峰值信噪比 透射率 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]