以视觉方法观测能见度为研究核心, 提出了基于双光源图像特征的夜间能见度观测方法, 完成在各种不同天气情况下, 对能见度的大范围、 高精度、 高鲁棒观测。 首先分析多次散射条件下, 光源图像亮度变化与大气消光之间的关系, 得出反演能见度的基本模型, 接着, 研究了准确获取与能见度相关的光源图像特征提取算法, 并提出了一种能消除光源波动的双光源能见度计算方法。 最后, 使用基于双光源图像特征的能见度观测系统在不同气象条件下进行实验, 结果表明, 在采用35 m基线长度, 设定观测上限为15 000 m时, 观测误差均小于20%, 能够满足气象与交通部门的要求。

Haze, rain and snow bring a lot of inconvenience in our daily life, especially produce serious potential safety hazard for night transport. In the present paper the authors propose the vision-based dual light sources visibility method to estimate night visibility. This method is significantly advantaged with wide range, high precision and low cost, and has a good robustness in many kinds of weather conditions. Firstly, the authors give the basic visibility estimation model under the atmosphere multiple scattering theory. Secondly, the authors propose the dual light sources method to remove the luminance fluctuations of light sources and the atmosphere light effect, and formulize the algorithm to accurately gain information of light sources from the dual light sources image. At last, the authors design the dual light sources system and conduct a long time experiments under various atmosphere conditions. The experiments show that, with the baseline of 35 m, the visibility range is up to 15 000 m, and relative error is below 20%. This method and system can satisfy the demand of meteorological department and transport agency.