传统图像去雾算法在处理亮度不均匀区域时可能会出现光晕现象,为了解决该问题,提出了一种基于边界限制的自适应双边滤波去雾方法。通过直方图分析方法,获得了明亮区域分割的阈值点,进而实现对明亮区域的分割,并求取了全局大气背景光的值。构造了自适应边界限制方法,获取了初始透射率图像,通过优化的自适应快速双边滤波方法对透射率图像进行了优化。运用改进的暗原色理论方法,获取最终的去雾结果。通过主观和客观实验分析,可得该方法在视觉效果和效率方面优于当前的去雾方法。

Traditional image dehazing algorithms usually appear halo phenomenon when processing regions with uneven brightness. In order to solve this problem, an adaptive bilateral filtering dehazing method based on boundary constraint is proposed. First, we use the histogram analysis method to obtain the threshold of bright region segmentation, thereby getting the global atmospheric background light. Second, a self-adaptive boundary limitation method is constructed to obtain the initial transmission image. The transmission map is optimized by an improved self-adaptive fast bilateral filtering method. Finally, the improved dark primary color theory method is used to obtain the final dehazing result. Through subjective and objective experimental analysis, we find that the proposed method is relatively superior to current dehazing methods in terms of visual effects and efficiency.