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Stereoscopic video quality assessment based on visual attention and just-noticeable difference models

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Abstract

With the consideration that incorporating visual saliency information appropriately can benefit image quality assessment metrics, this paper proposes an objective stereoscopic video quality assessment (SVQA) metric by incorporating stereoscopic visual attention (SVA) to SVQA metric. Specifically, based upon the multiple visual masking characteristics of HVS, a stereoscopic just-noticeable difference model is proposed to compute the perceptual visibility for stereoscopic video. Next, a novel SVA model is proposed to extract stereoscopic visual saliency information. Then, the quality maps are calculated by the similarity of the original and distorted stereoscopic videos’ perceptual visibility. Finally, the quality score is obtained by incorporating visual saliency information to the pooling of quality maps. To evaluate the proposed SVQA metric, a subjective experiment is conducted. The experimental result shows that the proposed SVQA metric achieves better performance in comparison with the existing SVQA metrics.

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Acknowledgments

This work has been supported in part by the Major State Basic Research Development Program of China (973 Program 2015CB351804), the National Science Foundation of China under Grant (Nos. 61472101, 61272386).

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Authors and Affiliations

  1. Harbin Institute of Technology, 92 West Dazhi Street, Harbin, 150001, China

    Feng Qi, Debin Zhao & Xiaopeng Fan

  2. National Engineering Lab for Video Technology, Peking University, Beijing, 100087, China

    Tingting Jiang

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  1. Feng Qi
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  2. Debin Zhao
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  3. Xiaopeng Fan
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  4. Tingting Jiang
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Correspondence to Xiaopeng Fan.

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Qi, F., Zhao, D., Fan, X. et al. Stereoscopic video quality assessment based on visual attention and just-noticeable difference models. SIViP 10, 737–744 (2016). https://doi.org/10.1007/s11760-015-0802-4

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  • DOI: https://doi.org/10.1007/s11760-015-0802-4

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