Coupled Deep Autoencoder for Single Image Super-Resolution

@article{Zeng2017CoupledDA,
  title={Coupled Deep Autoencoder for Single Image Super-Resolution},
  author={Kun Zeng and Jun Yu and Ruxin Wang and Cuihua Li and Dacheng Tao},
  journal={IEEE Transactions on Cybernetics},
  year={2017},
  volume={47},
  pages={27-37}
}
Sparse coding has been widely applied to learning-based single image super-resolution (SR) and has obtained promising performance by jointly learning effective representations for low-resolution (LR) and high-resolution (HR) image patch pairs. However, the resulting HR images often suffer from ringing, jaggy, and blurring artifacts due to the strong yet ad hoc assumptions that the LR image patch representation is equal to, is linear with, lies on a manifold similar to, or has the same support… 
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