• Corpus ID: 237375262

A survey on IQA

@article{Wang2021ASO,
  title={A survey on IQA},
  author={Lanjiang. Wang},
  journal={ArXiv},
  year={2021},
  volume={abs/2109.00347}
}
  • Lanjiang. Wang
  • Published 29 August 2021
  • Computer Science, Engineering
  • ArXiv
Image quality assessment(IQA) is of increasing importance for image-based applications. Its purpose is to establish a model that can replace humans for accurately evaluating image quality. According to whether the reference image is complete and available, image quality evaluation can be divided into three categories: full-reference(FR), reduced-reference(RR), and non-reference(NR) image quality assessment. Due to the vigorous development of deep learning and the widespread attention of… 

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