中文摘要：

为克服雾天能见度检测仪价格昂贵、检测范围小等缺点,该文结合雾天光线传输模型与摄像机几何光学模型提出一种交通能见度估计算法.该算法通过动态标定交通摄像机内外参数来计算路面区域内点到摄像机的距离,利用场景透射率得到大气消光系数并估计交通能见度.首先,算法基于活动图提取感兴趣区域,再根据区域内平均像素拟合曲线是否满足刃边函数对雾天进行识别;其次,通过暗原色先验原理估计交通场景中每一个点的透射率,并且选取道路上4组透射率差值最大的点对摄像机内部参数标定;然后,提取消失点及车道边缘线完成摄像机外部参数动态标定;最后,通过路面上点到摄像机的距离以及相应的场景透射率估计交通场景的能见度.该文将雾天多个交通场景下能见度值计算结果与人工观测、物理仪器测量等方法进行了比较,结果证明了该文方法的有效性与实时性.

英文摘要：

In order to solve the problems of costly instruments and small detection area in visibility detection,a traffic visibility estimation algorithm was proposed by combing light transmission model in fog with camera calibration geometrical optics model.The algorithm calculated the distance from point in road area to the camera by calibrating internal and external parameters dynamically,obtaining the atmospheric extinction coefficient and estimating the traffic visibility using scene transmittance.Firstly,interesting area was searched by activity map,and the fog weather was recognized by fitting curve of area average pixels whether meet the edge spread function or not.Secondly,transmittance value of each point in traffic scene was calculated by dark channel prior,and four group points of transmission difference maximum were selected to calibrate the internal parameters of the camera.Thirdly,vanishing point and boundary of the road were extracted to calibrate the camera external parameters dynamically.Finally,traffic visibility was estimated by using the distance from the point in road area to the camera and corresponding scene transmittance.In this paper,visibility estimation results are compared with corresponding data got by manual and physical equipment.We also verify the effectiveness and real-time of this proposed method.