Wavelet Siamese Network for Change Detection in Remote Sensing Images
- Resource Type
- Conference
- Authors
- Li, Tianhan; Xiong, Fengchao; Zheng, Wenbin; Li, Zhuanfeng; Zhou, Jun; Qian, Yuntao
- Source
- IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium Geoscience and Remote Sensing Symposium, IGARSS 2023 - 2023 IEEE International. :5455-5458 Jul, 2023
- Subject
- Aerospace
Components, Circuits, Devices and Systems
Fields, Waves and Electromagnetics
Geoscience
Signal Processing and Analysis
Wavelet transforms
Frequency-domain analysis
Semantics
Neural networks
Sensors
Remote sensing
Change detection
remote sensing image
Discrete Wavelet Transform
convolutional neural network
- Language
- ISSN
- 2153-7003
Change detection is a technique used to identify semantic differences between co-registered images of the same area captured at different times. However, current methods often overlook the fact that the low-frequency and high-frequency components of these images play distinct roles in change detection. Our method decomposes each feature map into its low-frequency and high-frequency components and then uses an attention mechanism to adjust the contribution of each component to handle different types of changes. Low-frequency information can help detect overall changes, and high-frequency information can enhance the integrity of the change boundaries. Experiments on the LEVIR-CD, WHU-CD and CLCD datasets show that our model outperforms the state-of-the-art method and the ablation study demonstrates that this approach improve the accuracy of the change detection.