一种无人机载高分辨率SAR图像目标快速检测方法  

A rapid detection method for UAV-borne high-resolution SAR image targets

作　　者：王中宝 尹奎英[1] WANG Zhongbao;YIN Kuiying(Nanjing Research Institute of Electronics Technology,Nanjing 210039,China)

机构地区：[1]中国电子科技集团公司第十四研究所,江苏南京210039

出　　处：《指挥控制与仿真》2023年第5期43-50,共8页Command Control & Simulation

摘　　要：针对无人机平台空间和资源有限、高分辨率SAR图像检测容易出现目标标注不准以及计算量过大等问题,提出一种无人机载高分辨率SAR图像目标快速检测方法。该方法首先利用双边滤波器抑制高分辨率SAR图像中存在的相干斑噪声和目标内部的非均匀起伏;然后进行一次大尺度的SLIC分割,通过对超像素单元粗糙度进行分析,对存在欠分割问题的超像素单元再进行一次小尺度的SLIC分割;最后对过分割的超像素单元进行合并处理,最终得到目标检测结果。实验结果表明,该方法不仅可以提升对高分辨率SAR图像目标的检测效率,改善SAR图像目标提取能力,还有利于发现部分人工方法容易遗漏的小目标,具有很好的工程应用价值。Aiming at the limited space and resources of the UAV platform,the inaccurate target labeling and excessive calculation amount of high-resolution SAR image detection,a rapid detection method for UAV-borne high-resolution SAR image targets is proposed.Firstly,a bilateral filter is used to suppress the coherent speckle noise and non-uniform undulation inside the target in the high-resolution SAR image.Then,a large-scale SLIC segmentation is performed,and a small-scale SLIC segmentation is performed on the superpixel unit with under segmentation problem by analyzing the roughness of the superpixel unit.Finally,the over-segmented superpixel units are combined to obtain the target detection results.The experimental results show that this method can not only improve the detection efficiency of high-resolution SAR image targets,improve the SAR image target extraction ability,but also help to find small targets that are easily missed by some manual methods,and has good engineering application value.

关 键 词：无人机 高分辨率SAR图像 SLIC 粗糙度 目标检测 

分 类 号：V279[航空宇航科学与技术—飞行器设计]