目的 在雾、霾等天气下，获取的图像受到大气粒子散射的影响而严重降质。针对这一问题，提出了一种基于双边滤波的单幅图像去雾算法。方法 此算法是以大气散射模型为基础。首先利用双边滤波保持边缘的平滑特性得到准确的大气耗散函数。其次，针对明亮区域失真的问题，本文提出了弱化明亮区域去雾的方法。最后，通过变换大气散射模型得到清晰的无雾图像。结果 大量实验结果表明，本算法恢复的图像清晰自然，尤其是在远景处和景深突变的边缘处的处理能取到很好的去雾效果。此外，其时间复杂度为图像大小的线性函数。结论 针对雾、霾天气下的降质图像，基于大气散射模型与双边滤波特性，本文提出了一种新的单幅图像去雾算法。实验结果表明，本算法能获得很好的去雾效果，尤其在细节处理的表现优于Tarel的去雾算法。同时，与He Kaiming的去雾算法相比，运行时间具有明显优势，有利于实现实时性技术应用。

Objective Images captured in foggy weather are often degraded due to atmospheric particles scatter. Concerning this issue, we present a new haze removal method from a single image based on bilateral filtering. Method This algorithm is based on the atmosphere scattering model. First, the accurate atmospheric veil is obtained by taking full use of the properties that bilateral filtering is available to preserve edges smoothly. Then, concerning the distortion of the bright portion,a weakening defogging strength method is proposed. Finally, the haze-free image is recovered by transforming the atmosphere scattering model. Result Many experiments show that images restored by this algorithm are clear and natural,especially at the portion for distant scene and for abrupt depth changes. In addition,the time complexity is only a linear function of the input image pixels. Conclusion Concerning degraded images captured in fog or haze weather,a new haze removal method from single image is proposed based on the atmosphere scattering model and the bilateral filter. Experiments show the algorithm can get an excellent performance for fog elimination,particularly better than Tarel's defogging algorithm in details. At the same time,compared with the defogging algorithm proposed by He Kaiming,it has a clear advantage for run time consideration,which is important to achieve real-time applicaiton.