基于局部一致性的马尔可夫随机场去雾

摘要

为克服暗通道先验的适用局限性,同时增强一阶马尔可夫随机场对图像全局信息的约束能力,在颜色衰减先验的基础上,提出了一种局部一致马尔可夫随机场(Markov random fields,MRF)单幅图像去雾算法.首先,结合颜色衰减和暗通道两先验假设的特征,获取普适性更强的介质传输图粗估计,然后利用基于颜色特征的图像局部一致块代替MRF的二阶及其高阶能量项来构造代价函数,达到优化介质传输图和获取最终去雾图像的目的.实验结果表明,所提算法可以获取细节保持更好且鲁棒性更强的去雾效果.%To overcome the limitation of dark channel prior's application,and strengthen the first-order Markov random fields (MRF) constraint ability of the global image information,a local consistent MRF defogging method is proposed based on color attenuation.First,combining with the advantages of color attenuation and dark channel priors,a more robust estimation of medium transmission is obtained.Then,the cost function is constructed with the color features based consistent blocks instead of Markov random fields' two-order and higher-order energy terms.Finally,the defogged image is obtained.The experimental results show that this method could improve the image resolution.