基于局部-全局特征耦合与边界引导的遥感图像建筑物变化检测  被引量:1

Building change detection in remote sensing images based onlocal-global feature coupling and boundary guidance

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作  者:郑剑[1] 柴岚康 于祥春 Zheng Jian;Chai Lankang;Yu Xiangchun(College of Information Engineering,Jiangxi University of Science&Technology,Ganzhou Jiangxi 341000,China)

机构地区:[1]江西理工大学信息工程学院,江西赣州341000

出  处:《计算机应用研究》2024年第6期1888-1892,共5页Application Research of Computers

基  金:江西省自然科学基金资助项目(20224BAB212013)。

摘  要:针对现有变化检测方法局部特征和全局特征难以兼顾、变化对象和背景之间分界模糊的问题,提出了一种基于局部-全局特征耦合与边界引导的遥感图像建筑物变化检测方法。该方法在编码阶段采用并行的卷积神经网络和Transformer分别提取遥感图像的局部特征与全局表示。在不同尺度下,使用局部-全局特征耦合模块融合局部特征和全局特征表示,以增强图像特征的表达能力。引入边界引导分支获取变化对象的先验边界信息,使其引导变化图突出建筑物的结构特征,促进边界精确定位。该方法在LEVIRCD和WHU数据集上进行实验验证,其F 1-score分别为91.25%和91.27%,IoU分别为83.90%和83.95%。实验结果表明,该方法在检测精度上有较大的提升,且具有良好的泛化能力。The existing change detection methods are difficult to balance local features and global features,and the boundary between change objects and backgrounds is blurred,so this paper proposed a remote sensing image building change detection method based on local-global feature coupling and boundary guidance.In the encoding stage,the method adopted parallel convolutional neural network and Transformer to extract the local features and global representation of remote sensing images,respectively.At different scales,the local-global feature coupling module fused local features and global feature representation to enhance the expression ability of image features.In addition,it introduced the boundary guidance branch to obtain the prior boundary information of the change objects,so that its guide change map can highlight the structural characteristics of the building and promote the accurate boundary location.This paper conducted experiments on the LEVIR-CD and WHU datasets,resulting in F 1-score of 91.25%and 91.27%,IoU of 83.90%and 83.95%,respectively.The experimental results show that the method has a great improvement in the detection accuracy and good generalization ability.

关 键 词:遥感图像 变化检测 卷积神经网络 TRANSFORMER 特征耦合 边界引导 

分 类 号:TP751.1[自动化与计算机技术—检测技术与自动化装置]

 

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