基于拐点线的大雾能见度检测算法

Visibility estimation algorithm for fog weather based on inflection point line

针对基于区域增长算法的能见度检测方法精度低和计算复杂度高的问题,提出一种基于拐点线(IPL)检测滤波器的能见度检测算法。首先,分析了拐点线所具有的各向异性、连续性和水平性等特征;然后,根据这些特征构建了一个拐点线检测滤波器,以提高拐点检测的精度和速度;最后,结合能见度计算模型和拐点线检测滤波器的检测结果计算大雾天气下的能见度值。与基于区域增长算法的能见度检测方法相比,该算法的运行时间和检测误差分别降低了80%和12.2%。实验结果表明,基于拐点线检测滤波器的能见度检测算法能够有效提高雾天能见度的检测精度,降低拐点定位的计算复杂度。

Concerning that the existing visibility estimation methods based on region growing method has shortcomings of low precision and high computational complexity, a new algorithm was proposed to measure the visibility based on Inflection Point Line （IPL）. Firstly, the three characteristics including anisotropy, continuity and level of inflection point line were analyzed. Secondly, a new 2-D filter to detect the IPL besed on the three characteristics was proposed to improve the accuracy and speed of the inflection point detection. Finally, the visibility of fog weather could be calculated through combing the visibility model and detection results of the proposed filter. Compared with the visibility estimation algorithm based on region growing, the proposed algorithm decreased the time cost by 80% and detection error by 12. 2%, respectively. The experimental results demonstrate that the proposed algorithm can effectively improve the detection accuracy, meanwhile reducing the computational complexity of positioning inflection points.