利用分割中值滤波和透射率补偿的图像去雾

为了增强雾天退化图像的质量，提出基于分割中值滤波和自适应透射率补偿的单幅图像去雾方法．首先提出分割中值滤波策略，通过对“暗通道先验+引导滤波”去雾方法估计的透射率进行滤波，去除其中不必要的纹理细节，同时保留深度突变的边缘信息；然后提出自适应透射率补偿方法，无须进行天空分割，而通过构造补偿函数对透射率进行提升，以校正明亮区域的色彩失真；同时给出简单有效的函数参数自动确定方法，提高了算法的适应性．由实验结果可以看出，该方法通过精确估计透射率，有效地增强了去雾图像的对比度，改善了天空区域的颜色失真．同时该方法适应性较强，对包含和不包含天空的图像，都可得到更为清晰的去雾结果．

Image dehazing by the segmenting median filter and transmission compensation

To enhance the quality of haze-degraded images, a single image dehazing approach based on the segmenting median filter and adaptive transmission compensation is proposed. First, a segmenting median filter is presented to smooth the transmission map estimated by the ‘dark channel prior + guided filter’ dehazing method, which aims to reduce the unnecessary edges or the texture of the transmission map but preserve the edges where the depth changes abruptly. Then, an adaptive compensation scheme is introduced to correct the transmission of bright areas by constructing a compensation function to avoid segmenting sky areas. Besides, we use a simple and effective way to determine parameters automatically, which improves the adaptability of our method. Experimental results show that our method enhances the image contrast and reduces the color distortion of sky areas by exploiting a more accurate estimation on the transmission map. In addition, our method has a better adaptability which can obtain sharper dehazed results both for the images with the sky and for those without the sky.