Making a “Completely Blind” Image Quality Analyzer

@article{Mittal2013MakingA,
  title={Making a “Completely Blind” Image Quality Analyzer},
  author={Anish Mittal and Rajiv Soundararajan and Alan Conrad Bovik},
  journal={IEEE Signal Processing Letters},
  year={2013},
  volume={20},
  pages={209-212}
}
An important aim of research on the blind image quality assessment (IQA) problem is to devise perceptual models that can predict the quality of distorted images with as little prior knowledge of the images or their distortions as possible. Current state-of-the-art “general purpose” no reference (NR) IQA algorithms require knowledge about anticipated distortions in the form of training examples and corresponding human opinion scores. However we have recently derived a blind IQA model that only… 
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