Satellite Video Super-resolution via Multi-Scale Deformable Convolution Alignment and Temporal Grouping Projection (TGRS)
This is the official implementation of our paper Satellite Video Super-resolution via Multi-Scale Deformable Convolution Alignment and Temporal Grouping Projection published on IEEE Transactions on Geoscience and Remote Sensing (TGRS).
- CUDA 10.0
- pytorch 1.x
- build DCNv2
Please download our dataset Jilin-189 Code:31ct
You can also train your dataset following the directory sturture below!
trainset--
| train--
| LR4x---
| 000.png
| ···.png
| 099.png
| GT---
| Bicubic4x---
testset--
| eval--
| LR4x---
| 000.png
| ···.png
| 099.png
| GT---
| Bicubic4x---
python main.py
python eval.py
If you find our work helpful, please cite:
@ARTICLE{9530280,
author={Xiao, Yi and Su, Xin and Yuan, Qiangqiang and Liu, Denghong and Shen, Huanfeng and Zhang, Liangpei},
journal={IEEE Transactions on Geoscience and Remote Sensing},
title={Satellite Video Super-Resolution via Multiscale Deformable Convolution Alignment and Temporal Grouping Projection},
year={2021},
volume={60},
number={},
pages={1-19},
doi={10.1109/TGRS.2021.3107352}
}
Our work is built upon RBPN and TDAN.
Thanks to the author for the source code !