图像能见度检测方法研究综述

Review of research on image visibility detection methods

在各种交通事故中,由雾霾等恶劣天气导致能见度降低引发的交通事故占比逐年增多,因此恶劣天气下能见度的检测成为一个亟待解决的问题。本文根据提取特征方式的不同,不仅将能见度检测的方法分为视觉检测法、仪器设备检测法和图像算法检测法,还归纳出能见度检测方法的发展历程。在分析和对比基于深度学习的能见度检测方法基础上,提出将最新的深度学习算法引入能见度检测是后续研究的重点。最后,总结现有能见度检测方法的不足和局限性,指出未来进一步研究的方向。

Among the various traffic accidents,the proportion of traffic accidents caused by the reduction of visibility caused by bad weather such as smog is increasing year by year,so the detection of visibility in bad weather has become an urgent problem to be solved.According to the different ways of extracting features,this paper not only divides the visibility detection methods into visual inspection methods,instrument and equipment detection methods and image algorithm detection methods,but also summarizes the development process of visibility detection methods.On the basis of analyzing and comparing the visibility detection methods based on deep learning,it is proposed that the introduction of the latest deep learning algorithm into visibility detection is the focus of follow-up research.Finally,the shortcomings and limitations of existing visibility detection methods are summarized,and the direction of further research in the future is pointed out.