Remote sensing image super-resolution (SR) fundamentally relies on effective feature representation learning. However, the existing methods that adopt mainstream architecture designs, such as transformer and state space model (SSM), are often restricted by two factors when dealing with the SR of remote sensing images....
Kang-Hui Zhao, Tao Lu, Jia-Ming Wang et al.· IEEE Transactions on Geoscie...· 0 citations
LEDGNet is presented, a Lightweight, Edge-knowledge- Distillation-Guided CD Network, that reconciles accuracy, boundary fidelity, and efficiency and is well-suited for high-efficiency remote sensing monitoring.
Tingyu Ji, Yixin Chen, Ruiqian Zhang et al.· ISPRS Annals of the Photogra...· 0 citations
A frequency-aware transformer module is designed to leverage the fast Fourier transform for explicit high-frequency component restoration, thereby overcoming the frequency bias inherent in spatial-domain models and effectively recovering intricate structural details.
Kangli Zeng, Hang Hu, Ying Yu et al.· IEEE Journal of Selected Top...· 0 citations
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