锚框策略匹配的SSD飞机遥感图像目标检测  

Target Detection of SSD Aircraft Remote Sensing Images Based on Anchor Frame Strategy Matching

作　　者：王浩桐 郭中华 WANG Haotong;GUO Zhonghua(School of Physics and Electronic and Electrical Engineering,Ningxia University,Yinchuan 750021,China;Key Laboratory of Desert Information Intelligent Sensing,Ningxia University,Yinchuan 750021,China)

机构地区：[1]宁夏大学物理与电子电气工程学院,银川750021 [2]宁夏大学沙漠信息智能感知重点实验室,银川750021

出　　处：《计算机科学与探索》2022年第11期2596-2608,共13页Journal of Frontiers of Computer Science and Technology

基　　金：宁夏自然科学基金(2020AAC03026);宁夏大学研究生创新研究项目(GIP2020075)。

摘　　要：针对当前飞机遥感图像目标检测算法的精度和实时性不能兼顾的问题,提出了基于SSD的锚框尺度密集化和锚框策略匹配目标检测算法。该算法选用经过改进后的深度残差网络替代SSD算法原有的特征提取网络。结合飞机遥感图像存在小尺度且密集的特点,重新设计了锚框尺度大小、比例和额外增加了一个包含两种尺度的特征层。而后对各个特征层进行锚框密集化操作使得特征层的锚框铺设密度基本相等,提高不同尺度的锚框匹配到真实目标的概率。在不同尺度的正样本锚框数量差距较大的问题上,提出了一种使得不同尺度的正样本锚框数量趋向于总体正样本平均值的锚框策略匹配方法,一定程度上提高训练的有效性和目标检测的鲁棒性。在飞机遥感数据集上进行相关实验,精度均值达到91.15%,每秒帧率为33.4。结果表明,改进后的算法不仅可以在增加较少训练参数的基础上提升检测精度,还能保留SSD算法的实时检测性。Aiming at the problem that the accuracy and real-time performance of current aircraft remote sensing image target detection algorithms cannot be balanced,a target detection algorithm based on single shot MultiBox detector(SSD)is proposed for anchor frame scale densification and anchor frame strategy matching.The algorithm uses an improved deep residual network to replace the original feature extraction network of the SSD algorithm.Combined with the small-scale and dense features of aircraft remote sensing images,this paper redesigns the size and proportion of anchor frame and adds a feature layer containing two scales.Then,the anchor frame densification operation is performed on each feature layer to make the anchor frame laying density of the feature layer basically equal,and to improve the probability of matching the anchor frames of different scales to the real target.On the issue of the large gap in the number of positive sample anchor frames of different scales,an anchor frame strategy matching method that makes the number of positive sample anchor frames of different scales tend to the overall positive sample average is proposed,which improves the effectiveness of training and robustness of target detection to a certain extent.Related experiments are conducted on the aircraft remote sensing dataset,the average precision reaches 91.15%,and the frame per second is 33.4.The results show that the improved algorithm can not only increase the detection accuracy on the basis of adding fewer training parameters,but also retain the real-time detectability of the SSD algorithm.

关 键 词：目标检测 遥感图像 实时检测 锚框匹配 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]