Deep Multi-Scale Features Learning for Distorted Image Quality Assessment

@article{Zhou2021DeepMF,
  title={Deep Multi-Scale Features Learning for Distorted Image Quality Assessment},
  author={Wei Zhou and Zhibo Chen},
  journal={2021 IEEE International Symposium on Circuits and Systems (ISCAS)},
  year={2021},
  pages={1-5}
}
  • Wei Zhou, Zhibo Chen
  • Published 1 December 2020
  • Computer Science
  • 2021 IEEE International Symposium on Circuits and Systems (ISCAS)
Image quality assessment (IQA) aims to estimate human perception based image visual quality. Although existing deep neural networks (DNNs) have shown significant effectiveness for tackling the IQA problem, it still needs to improve the DNN- based quality assessment models by exploiting efficient multi- scale features. In this paper, motivated by the human visual system (HVS) combining multi-scale features for perception, we propose to use pyramid features learning to build a DNN with… 

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