基于天空区域分割与置信度图导向融合的去雾方法研究

基于暗通道先验的去雾算法总是存在复原结果中天空区域处理不佳等问题，为了进一步优化对传输函数的估计，本文提出一种基于置信度图导向融合的传输函数优化方法。首先，将雾天图像的天空区域分离出来，以达到对天空区域的优化；计算窗口级暗通道与像素级暗通道，以平滑传输函数在物体边缘并保留小于窗口尺寸的细节特征；最后，计算窗口级暗通道与像素级暗通道之间的置信度图，以其为导向对两者进行融合得到优化的传输函数图，实现图像去雾。实验结果表明，本文算法可达到很好的复原结果优化效果。

Dehazing algorithm based on sky region segmentation and reliability map guided fusion

The sky region in the restoration results for dehazing algorithm based on dark channel prior always exists the drawbacks such as halos. In order to further optimize the estimation of transmission function,this paper proposes a transmission function optimization method based on reliability map guided fusion.Firstly,the sky region of the hazy image is segmented and optimized;the window level dark level channel and pixel dark level channel are calculated to ensure the smoothness of the transmission function at the edge of the objects and the outstanding of the detail features smaller than the window size;finally,the reliability map between window level dark channel and pixel level dark channel is calculated.The refine transmission function map is obtained to realize image dehazing by the fusion of these two dark channels through the guidance of the reliability map.The experimental results show that the estimation of transmission function optimized by the proposed method could achieve fine image dehazing effects.