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Quality assessment metric of stereo images considering cyclopean integration and visual saliency

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journal contribution
posted on 2016-10-20, 10:14 authored by Jiachen Yang, Yafang Wang, Baihua LiBaihua Li, Wen Lu, Qinggang MengQinggang Meng, Zhihan Lv, Dezong Zhao, Zhiqun Gao
In recent years, there has been great progress in the wider use of three-dimensional (3D) technologies. With increasing sources of 3D content, a useful tool is needed to evaluate the perceived quality of the 3D videos/images. This paper puts forward a framework to evaluate the quality of stereoscopic images contaminated by possible symmetric or asymmetric distortions. Human visual system (HVS) studies reveal that binocular combination models and visual saliency are the two key factors for the stereoscopic image quality assessment (SIQA) metric. Therefore inspired by such findings in HVS, this paper proposes a novel saliency map in SIQA metric for the cyclopean image called “cyclopean saliency”, which avoids complex calculations and produces good results in detecting saliency regions. Moreover, experimental results show that our metric significantly outperforms conventional 2D quality metrics and yields higher correlations with human subjective judgment than the state-of-art SIQA metrics. 3D saliency performance is also compared with “cyclopean saliency” in SIQA. It is noticed that the proposed metric is applicable to both symmetric and asymmetric distortions. It can thus be concluded that the proposed SIQA metric can provide an effective evaluation tool to assess stereoscopic image quality.

Funding

This work was supported in part by National Natural Science Foundation of China (No. 61471260 and No. 61271324 ), and Natural Science Foundation of Tianjin: 16JCYBJC160 0 0.

History

School

  • Science

Department

  • Computer Science

Published in

Information Sciences

Volume

373

Pages

251 - 268

Citation

YANG, J. ... et al, 2016. Quality assessment metric of stereo images considering cyclopean integration and visual saliency. Information Sciences, 373, pp. 251-268.

Publisher

© Elsevier

Version

  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

2016-09-01

Publication date

2016

Notes

This paper was accepted for publication in the journal Information Sciences and the definitive published version is available at http://dx.doi.org/10.1016/j.ins.2016.09.004.

ISSN

0020-0255

Language

  • en