计算机与数字工程2025，Vol.53Issue(3)：795-802,8.DOI:10.3969/j.issn.1672-9722.2025.03.031
基于高分辨率遥感图像的道路车辆定位研究
Research on Road Vehicle Location Based on High Resolution Remote Sensing Image
摘要
Abstract
With the continuous progress and maturity of satellite launch technology,high-resolution remote sensing image technology has also continued to improve,the acquisition of remote sensing image data has also become easier and more conve-nient,then the features of road vehicles extracted from remote sensing images are becoming clearer.Road vehicle positioning based on high-resolution remote sensing images can quickly identify the number of vehicles in a relatively wide range.This paper provides an important solution for intelligent traffic control or traffic emergencies.Based on the provided remote sensing images of Xuanwu district,under the framework of TensorFlow based machine learning,this paper uses the SSD object detection algorithm to conduct research on the localization of road vehicles.However,considering the large amount of parameters involved in the network structure when using the SSD network framework,part of the VGG network designed and used in the SSD network framework is replaced by the depthwise separable convolution,which greatly reduces the amount of parameters required by the algorithm and saves the time required to obtain the result.Finally,the multi-index analysis of the experimental results shows that the proposed method has high accuracy in the area with good illumination conditions and wide vision.The accuracy of road vehicle positioning detection is slightly lower under the interference of light,vegetation and buildings.The experimental results are superior to those of YOLO V2 and YO-LO V3.关键词
遥感技术/深度学习/卷积神经网络/目标检测/图像处理Key words
remote sensing technique/deep learning/convolutional neural networks/object detection/image processing分类
信息技术与安全科学引用本文复制引用
王嘉怡,田瑶,徐昇..基于高分辨率遥感图像的道路车辆定位研究[J].计算机与数字工程,2025,53(3):795-802,8.基金项目
国家自然科学基金青年科学基金项目(编号:62102184) （编号:62102184）
江苏省自然科学基金青年科学基金项目(编号:BK20200784) （编号:BK20200784）
中国博士后科学基金面上项目(编号:2019M661852) （编号:2019M661852）
江苏省高等学校大学生创新创业训练计划项目"针对遥感图像的改进生成对抗网络超分辨率重建"(编号:202210298042Z) （编号:202210298042Z）
南京林业大学大学生实践创新训练项目"基于深度学习的树木图像识别技术研究"(编号:2021NFUSPITP0264)资助. （编号:2021NFUSPITP0264）
