| Autor: |
Jiawei Xiong, Feng Liu, Xingyuan Wang, Chaozhong Yang |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Sensors, Vol 24, Iss 4, p 1268 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
1424-8220 |
| DOI: |
10.3390/s24041268 |
| Popis: |
To address the challenges of handling imprecise building boundary information and reducing false-positive outcomes during the process of detecting building changes in remote sensing images, this paper proposes a Siamese transformer architecture based on a difference module. This method introduces a layered transformer to provide global context modeling capability and multiscale features to better process building boundary information, and a difference module is used to better obtain the difference features of a building before and after a change. The difference features before and after the change are then fused, and the fused difference features are used to generate a change map, which reduces the false-positive problem to a certain extent. Experiments were conducted on two publicly available building change detection datasets, LEVIR-CD and WHU-CD. The F1 scores for LEVIR-CD and WHU-CD reached 89.58% and 84.51%, respectively. The experimental results demonstrate that when utilized for building change detection in remote sensing images, the proposed method exhibits improved robustness and detection performance. Additionally, this method serves as a valuable technical reference for the identification of building damage in remote sensing images. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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