[TGRS 2025] GDSR: Global-Detail Integration through Dual-Branch Network with Wavelet Losses for Remote Sensing Image Super-Resolution

     

Network

Loss

Training and Testing

Please use BasicSR, it is an open-source image super-resolution toolbox based on PyTorch.

Citation

If you find this work useful, please consider citing:

@ARTICLE{GDSR,
  author={Zhu, Qiwei and Li, Kai and Zhang, Guojing and Wang, Xiaoying and Huang, Jianqiang and Li, Xilai},
  journal={IEEE Transactions on Geoscience and Remote Sensing}, 
  title={GDSR: Global-Detail Integration Through Dual-Branch Network With Wavelet Losses for Remote Sensing Image Super-Resolution}, 
  year={2025},
  volume={63},
  number={},
  pages={1-16},
  keywords={Transformers;Wavelet transforms;Image reconstruction;Computational modeling;Remote sensing;Computer architecture;Feature extraction;Superresolution;Convolutional neural networks;Adaptation models;Dual-branch;global-detail reconstruction;remote sensing image (RSI);super-resolution (SR)},
  doi={10.1109/TGRS.2025.3617006}}

Reference

Some of the codes in this repo are borrowed from:

Thanks to their great work.