利用大气光图改进暗原色去雾效果

Improvement of Image Haze Removal Based on Dark Channel Prior with Airlight Map

为了解决暗原色先验去雾算法去雾后图像出现饱和区域和亮度过低的现象,本文使用"大气光图"来代替原算法中的大气光值进行去雾。即去雾时使用的大气光值是像素点的位置函数,解决了整幅图像使用同一大气光值导致的上述问题。假设图像中亮度变化方向是沿着4个基本方向,并且亮度沿着亮度变化方向分段单调变化,采用分段线性插值的方法生成渐变的大气光图。新算法原理简单,单帧图像的去雾时间没有明显的增加,并且有效地改善了暗原色去雾算法的去雾效果。

To solve the problems such as pixel value saturation and low brightness in the result of Dark channel prior haze removal algorithm, we proposed ＂Airlight Map＂ instead of the airlight value in the original algorithm. That is to say, we used different airlight values for each pixel of the image during dehaze process. Thus the problem caused by using only one airlight value in the whole image could be solved. We assumed that the directions of brightness change in one image can be classified into four basic directions, and the airlight value was piecewise monotone along the direction of brightness change. Therefore, we generated the Airlight Map using piecewise linear interpolation. The proposed method is simple in principle, and the dehaze time dose not increase notably. At the same time, better haze removal results are obtained using our method.