Nonlinear radiometric distortion, orientation reversal, and image rotation considerably affect multimodal image matching performance in remote sensing. Furthermore, existing multimodal image matching algorithms are highly complex and inefficient. We addressed these issues by developing a reliable matching method consid...
Li Xue, Ye-Hua Sheng, Shu-Wen Yang et al.· IEEE Journal of Selected Top...· 0 citations
Change detection under Gaussian noise is challenging because noise perturbs spectral clustering and posterior inference. This study presents a scene-adaptive weakly supervised framework that combines self-supervised single-image restoration with posterior-probability change modeling. A channel-spatial attention aggrega...
Rui Zhu, Jia-Xin Song, Yi-Kun Li et al.· Electronics· 0 citations
Landslide detection is essential for geological disaster mitigation, yet existing deep learning methods still struggle with the high cost of global feature modeling, limited receptive fields in window-based attention, and insufficient fusion of local and global information. To address these challenges, we propose MTTNe...
Jia-Xin Song, Shu-Wen Yang, Hao Zhu et al.· IEEE Geoscience and Remote S...· 0 citations
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