针对暗通道先验在天空区域出现轮廓效应和色彩失真等问题，提出天空区域分割和不同区域透射率映射的去雾算法。首先，利用自适应阈值法粗略分割图像天空区域，在天空区域中完成大气光值的估计。其次，结合超像素分割方法改进暗通道，获得初始透射率，利用导向滤波的方法得到细化透射率，对细化透射率进行自适应阈值分割，并保留最大连通域实现天空区域的精细分割。最后，针对天空和非天空区域提出不同的透射率映射方法，得到最终透射率，并利用大气散射模型复原图像。实验结果表明，恢复图像在主观视觉和客观指标方面均表现出色。算法有效地解决了暗通道先验算法容易在天空区域失效的缺陷，可以恢复比较自然的天空，减弱了边缘区域的halo效应。

To solve the contour effect and color distortion problems in the sky area of the dark channel prior algorithm， a dehazing algorithm for sky area segmentation and transmission mapping of different areas is proposed. First， the sky area of an image is roughly segmented using the adaptive threshold method， and the atmospheric light value is estimated in the sky area. Second， the dark channel is improved by applying the super-pixel segmentation method to obtain the initial transmission， and refined transmission is obtained using the guided filtering method. Adaptive threshold segmentation is performed on the refined transmission， and the largest connected domain is retained to achieve fine segmentation of the sky area. Finally， different transmission mapping methods are proposed for the sky and non-sky areas to obtain the final transmission， and the atmospheric scattering model is used to restore the image. Experimental results showed that the restored image performed well in terms of both subjective vision and objective indicators. This effectively solves the defect whereby the dark channel prior algorithm easily fails in the sky area. The proposed dehazing algorithm can restore a more natural sky and weaken the halo effect in the edge area.