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ASDDPM-Adaptive-Semantic-Enhanced-DDPM

Since many people pay attention to this project, I have totally updated this project to fertilize easy test. Please follow run.sh to train and test this model. Thanks for your attention. And I have also uploaded my processed datasets on OLI2MSI and ALSAT.

šŸ”„ This paper is accepted by IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. While, it's my second jstar which takes me more than one year from completion to acceptance. I feel quite exhausted. Whatever, congradualations.

The code for Adaptive Semantic-Enhanced Denoising Diffusion Probabilistic Model for Remote Sensing Image Super-Resolution, the other models shown in the experiments could be refered to Remote-Sensing-Super-resolution-Model-Collection.

Models

Dataset

The experimental datasets, OLI2MSI and Alsat, their official version could be obtained from:

I make few manipulation based on them. The processed datasets could be downloaded at https://pan.baidu.com/s/1l2CXgEJGVBGcOonUBnOLfg code bean. Put them into ./dataset like the demos.

Usage

Train

  1. Download the RRDB pre-train model from link and put it into the right place (./models/LREncoder/) according to the guidance in this link. https://pan.baidu.com/s/1siWepPn2pVFC3SGyk1wuJg codeļ¼šbean
  2. Change the model name and data information in the option.py. More information could be obtained from run.sh

python trainer.py

Test

  1. Put pre-trained model into 'pre_train'
  2. Change the model name in the option.py

python test.py

Weight

Our pre-train ASDDPM and RRDB model on OLI2MSI and ALSAT could be downloaded from linkļ¼šhttps://pan.baidu.com/s/1siWepPn2pVFC3SGyk1wuJg codeļ¼šbean

A guidance file is also shared in this link, please put the pre-train model to the right place according to the guidance. (Attention: the code could run only after the RRDB pre-train model is put in the right place.)

Cite

@ARTICLE{10763472,
  author={Sui, Jialu and Ma, Xianping and Zhang, Xiaokang and Pun, Man-On and Wu, Hao},
  journal={IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing}, 
  title={Adaptive Semantic-Enhanced Denoising Diffusion Probabilistic Model for Remote Sensing Image Super-Resolution}, 
  year={2025},
  volume={18},
  pages={892-906},
}
@article{sui2023gcrdn,
  title={Gcrdn: Global context-driven residual dense network for remote sensing image super-resolution},
  author={Sui, Jialu and Ma, Xianping and Zhang, Xiaokang and Pun, Man-On},
  journal={IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  year={2023},
  publisher={IEEE}
}
@article{sui2024denoising,
  title={Denoising Diffusion Probabilistic Model with Adversarial Learning for Remote Sensing Super-Resolution},
  author={Sui, Jialu and Wu, Qianqian and Pun, Man-On},
  journal={Remote Sensing},
  volume={16},
  number={7},
  pages={1219},
  year={2024},
  publisher={MDPI}
}

Be free to create a issue if you have any questions! Sometimes I could not answer the questions on time. But I promise I will response to all the issues when I am free.šŸ¤—