App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 6

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

Zheng Jian
Chai Lankang
Yu Xiangchun
College of Information Engineering, Jiangxi University of Science & Technology, GanZhou Jiangxi 341000, China
DOI: 10.19734/j.issn.1001-3695.2023.09.0407

Abstract

The existing change detection methods are difficult to balance local features and global features, and the boundary between change objects and backgrounds is blurred, 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 F1-score of 91.25% and 91.27%, and 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.

Foundation Support

江西省自然科学基金资助项目(20224BAB212013)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.09.0407
Publish at: Application Research of Computers Accepted Paper, Vol. 41, 2024 No. 6

Publish History

[2023-11-16] Accepted Paper

Cite This Article

郑剑, 柴岚康, 于祥春. 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 [J]. 计算机应用研究, 2024, 41 (6). (2024-04-10). https://doi.org/10.19734/j.issn.1001-3695.2023.09.0407. (Zheng Jian, Chai Lankang, Yu Xiangchun. Building change detection in remote sensing images based on local-global feature coupling and boundary guidance [J]. Application Research of Computers, 2024, 41 (6). (2024-04-10). https://doi.org/10.19734/j.issn.1001-3695.2023.09.0407. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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