• Corpus ID: 239049868

Toward Real-world Image Super-resolution via Hardware-based Adaptive Degradation Models

@article{Ma2021TowardRI,
  title={Toward Real-world Image Super-resolution via Hardware-based Adaptive Degradation Models},
  author={Rui Ma and Johnathan Czernik and Xian Du},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.10755}
}
Most single image super-resolution (SR) methods are developed on synthetic low-resolution (LR) and high-resolution (HR) image pairs, which are simulated by a predetermined degradation operation, e.g., bicubic downsampling. However, these methods only learn the inverse process of the predetermined operation, so they fail to super resolve the real-world LR images; the true formulation deviates from the predetermined operation. To address this problem, we propose a novel supervised method to… 

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