【摘要】 针对雾天环境下图像清晰度降低以及色调偏移问题,提出一种基于暗原色先验的单幅图像快速去雾算法。首先使用灰度开运算代替最小值滤波得到粗略暗通道图,根据方差标记出雾天图像各个景深突变区的位置,并对突变区的暗原色值进行细化求解;其次求解出透射率的粗略估计并使用引导滤波来进行优化;然后使用一种自适应的容差机制对天空等明亮区域的透射率进行动态修正;最后利用大气散射模型复原出无雾图像。实验结果表明,与几种典型的图像去雾算法相比,所提算法具有较快的处理速度,同时得到的复原图像细节突出、色彩丰富。更多还原

【Abstract】 To solve the bad influence on images in foggy days such as decrease of definition and color deviation problem,a fast dehazing method for single image based on dark channel prior was proposed.Firstly,minimum was replaced by grayscale opening operation to obtain rough dark channel image,and the regions which showed the sudden changes in the foggy image were marked based on the variance so that small window was used to correct the dark channel value in these areas.Next,the rough transmission map was acquired and the guided filter was adopted to refine the transmission.Then,the transmission of sky or other light area was corrected dynamically by using a self-adapting tolerance mechanism.Finally,the final haze-free image was restored from the atmospheric scattering model.The experimental results demonstrate that,compared with other representative dehazing algorithms,the proposed method can achieve a faster processing speed and provide more detailed restored image with good color effect.更多还原