低分辨率暗弱光斑图像的目标识别技术研究  

Research on target recognition technology for low resolution dim spot images

作　　者：李欣阳 李智[1] Li Xinyang;Li Zhi(College of Electronics and Information Engineering,Sichuan University,Chengdu 610065,China)

机构地区：[1]四川大学电子信息学院,成都610065

出　　处：《现代计算机》2024年第9期9-16,共8页Modern Computer

摘　　要：针对新一代激光雷达对远距离、高速运动目标实现超快发现、检测与识别的需求,解决自然环境多变、目标暗弱且高速运动导致图像分辨率低的问题,鉴于传统光学和传统网络无法对目标实现高精准的识别,提出低分辨率暗弱光斑图像的深度层次轮廓识别网络LRDSI-DLCRN,该网络引入全局权重编码模块,采用子像素卷积进行上采样,丰富了不同层次边缘结构特征的相关性,在公开数据集PASCAL VOC 2012和真实环境采集的Spotcraf数据集上的效果都优于其它流行算法。In response to the demand of the new generation of LiDAR for ultra fast detection,detection,and recognition of long-distance and high-speed moving targets,and to solve the problem of low image resolution caused by the changing natural envi-ronment,dim targets,and high-speed motion,traditional optics and networks cannot achieve high-precision recognition of targets.Therefore,a deep level contour recognition network LRDSI-DLCRN for low resolution dim spot images is proposed,The network in-troduces a global weight encoding module and uses sub pixel convolution for upsampling,enriching the correlation of edge struc-ture features at different levels.The performance on the public dataset PASCAL VOC 2012 and the real environment collected Spotcraf dataset is superior to other popular algorithms.

关 键 词：低分辨率光斑图像 轮廓识别 子像素卷积 

分 类 号：TN957.52[电子电信—信号与信息处理]