Visual attention based image quality assessment

@article{Guo2011VisualAB,
  title={Visual attention based image quality assessment},
  author={Anan Guo and Debin Zhao and Shaohui Liu and Xiaopeng Fan and Wen Gao},
  journal={2011 18th IEEE International Conference on Image Processing},
  year={2011},
  pages={3297-3300}
}
Inspired by the success of structural similarity index (SSIM), some image quality assessment (IQA) methods have been developed recently. To achieve better performance, this paper proposes a new visual attention (VA) model that combines saliency based VA and visual importance based VA, under the assumptions that humans often pay more attention to the regions with important content in the beginning of evaluating a given image and then the regions with poor quality. Then the proposed VA model is… CONTINUE READING
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H.R.Sheikh and E.P.Simoncalli, “Image quality assessment: From error visibility to structural similarity

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