Wavelet siamese network for change detection in remote sensing images
IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM(2023)
摘要
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.
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关键词
Change detection,remote sensing image,Discrete Wavelet Transform,convolutional neural network
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