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MSF-UNet: A Mamba-based Spatial-Frequency Feature Fusion U-Net for Unsupervised Change Detection in SAR Images
ZHANG Yu, ZHUANG Huifu, ZHANG Xiang, TAN Zhixiang, LIU Yuhao, SHANG Jingjie, GUO Mingming
Journal of Geo-information Science
, 2025, 27(
9
): 2213-2229. DOI:
10.12082/dqxxkx.2025.250269
参数
方法
DDNet
FCD-GAN
SNUNet-CD
TransUNet
CDRL-SA
ELCG-Net
MSF-UNet
参数量/M
0.067
170.324
12.035
93.231
44.114
10.570
108.847
浮点运算次数/G
0.002
9.609
0.857
0.503
0.818
1.931
0.394
训练时间/(s/轮)
12.178
90.411
32.848
48.163
32.738
36.327
28.433
Tab. 4
Model parameter quantities and floating-point operation counts of different methods
Other figure/table from this article
Fig. 1
The overall framework of the proposed method
Fig. 2
Flowchart of the DSCF method
Fig. 3
Structural diagram of the MSF-UNet model
Fig. 4
Images and reference change map of the Handan dataset
Fig. 5
Images and reference change map of the Yellow River dataset
Fig. 6
Impact analysis of threshold m on
F
1
_Score
of change detection results
Fig. 7
Change detection results of different methods on the Handan dataset
Tab. 1
Quantitative analysis results of different methods on the Handan dataset
Fig. 8
Change detection results of different methods on the Yellow River dataset
Tab. 2
Quantitative analysis results of different methods on the Yellow River dataset
Fig. 9
Change detection results of the ablation experiment on the Handan dataset
Tab. 3
Evaluation metric results of ablation experiments on the Handan dataset