结合暗通道先验的单幅图像快速去雾算法

A Fast Single Image Dehazing Algorithm Based on Dark Channel Prior

基于暗通道先验的单幅图像去雾算法对天空区域的恢复效果不佳,且运行效率较低.为此,文中提出了一种快速、有效的单幅图像去雾算法.该算法首先根据颜色衰减先验建立场景深度模型,并基于场景深度模型估计透射率,再基于局部一致性和暗通道先验得到粗透射率;然后利用图像融合的方法,将基于场景深度模型估计的透射率与粗透射率融合,实现天空区域透射率的修正;最后采用导向滤波细化的透射率复原图像,并对复原图像进行色调调整.实验结果表明,文中算法运行效率高,并且有效地提高了复原图像的清晰度和对比度.

A fast and effective single image dehazing algorithm is proposed in this paper because of the low efficiency and the poor result in the sky region on the basis of the dark channel prior. Firstly,according to the color attenuation prior,the scene depth model is established to estimate the transmittance. Then,the rough transmittance is obtained on basis of local consistency and the dark channel prior. After that,the rough transmittance and the transmittance estimated by the scene depth model are fused to correct the transmittance of the sky region. Finally,the image is restored by means of the transmittance refined by guided filter,and the tone mapping is applied to the restored image. Experiments show that the proposed algorithm has high efficiency,which can also effectively improve the visibility and contrast of the restored image.