Eagle-Vision-Based Object Detection Method for UAV Formation in Hazy Weather  

一种基于鹰视觉的雾霾天气无人机编队目标检测方法

作　　者：LI Hao DENG Yimin XU Xiaobin SUN Yongbin WEI Chen 李皓;邓亦敏;徐小斌;孙永斌;魏晨(北京航空航天大学自动化科学与电气工程学院,中国北京100083)

机构地区：[1]School of Automation Science and Electrical Engineering,Beihang University,Beijing 100083,P.R.China

出　　处：《Transactions of Nanjing University of Aeronautics and Astronautics》2020年第4期517-527,共11页南京航空航天大学学报（英文版）

基　　金：the Science and Technology Innovation 2030-Key Projects(Nos.2018AAA0102303,2018AAA0102403);the Aeronautical Science Foundation of China(No.20175851033);the National Natural Science Foundation of China(Nos.U1913602,U19B2033,91648205,61803011).

摘　　要：Inspired by eagle’s visual system,an eagle-vision-based object detection method for unmanned aerial vehicle(UAV)formation in hazy weather is proposed in this paper.To restore the hazy image,the values of atmospheric light and transmission are estimated on the basis of the signal processing mechanism of ON and OFF channels in eagle’s retina.Local features of the dehazed image are calculated according to the color antagonism mechanism and contrast sensitivity function of eagle’s visual system.A center-surround operation is performed to simulate the response of reception field.The final saliency map is generated by the Random Forest algorithm.Experimental results verify that the proposed method is capable to detect UAVs in hazy image and has superior performance over traditional methods.本文提出了一种仿鹰眼视觉特性的雾霾天气下无人机编队目标检测算法。通过模拟鹰视网膜中ON和OFF通路的视觉信号处理机制,对大气光与透射率的值进行估计从而复原雾霾图像。同时利用鹰视觉系统的颜色拮抗机制与对比度敏感函数提取除雾图像下的目标特征,模拟中央-周边结构感受野特性对特征进行整合,最后通过随机森林算法生成目标显著图以进行目标检测。实验结果表明本文提出的算法能够有效检测出雾霾天气下无人机编队场景中的无人机目标,与其他传统方法相比,本文算法具有更好的检测效果。

关 键 词：object detection eagle visual system UAV formation image dehazing 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]