Toward a Blind Deep Quality Evaluator for Stereoscopic Images Based on Monocular and Binocular Interactions

@article{Shao2016TowardAB,
  title={Toward a Blind Deep Quality Evaluator for Stereoscopic Images Based on Monocular and Binocular Interactions},
  author={Feng Shao and Weijun Tian and Weisi Lin and Gangyi Jiang and Qionghai Dai},
  journal={IEEE Transactions on Image Processing},
  year={2016},
  volume={25},
  pages={2059-2074}
}
During recent years, blind image quality assessment (BIQA) has been intensively studied with different machine learning tools. Existing BIQA metrics, however, do not design for stereoscopic images. We believe this problem can be resolved by separating 3D images and capturing the essential attributes of images via deep neural network. In this paper, we propose a blind deep quality evaluator (DQE) for stereoscopic images (denoted by 3D-DQE) based on monocular and binocular interactions. The key… CONTINUE READING

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A perceptual metric for stereoscopic image quality assessment based on the binocular energy

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