Group MAD Competition? A New Methodology to Compare Objective Image Quality Models

@article{Ma2016GroupMC,
  title={Group MAD Competition? A New Methodology to Compare Objective Image Quality Models},
  author={Kede Ma and Qingbo Wu and Zhou Wang and Zhengfang Duanmu and Hongwei Yong and Hongliang Li and Lei Zhang},
  journal={2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2016},
  pages={1664-1673}
}
Objective image quality assessment (IQA) models aim to automatically predict human visual perception of image quality and are of fundamental importance in the field of image processing and computer vision. With an increasing number of IQA models proposed, how to fairly compare their performance becomes a major challenge due to the enormous size of image space and the limited resource for subjective testing. The standard approach in literature is to compute several correlation metrics between… CONTINUE READING
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