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Title: Quality assessment metric of stereo images considering cyclopean integration and visual saliency
Authors: Yang, Jiachen
Wang, Yafang
Li, Baihua
Lu, Wen
Meng, Qinggang
Lv, Zhihan
Zhao, Dezong
Gao, Zhiqun
Keywords: Binocular combination
Human visual system
Stereoscopic image quality assessment
Visual attention
Issue Date: 2016
Publisher: © Elsevier
Citation: YANG, J. ... et al, 2016. Quality assessment metric of stereo images considering cyclopean integration and visual saliency. Information Sciences, 373, pp. 251-268.
Abstract: 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.
Description: 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.
Sponsor: 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.
Version: Accepted for publication
DOI: 10.1016/j.ins.2016.09.004
URI: https://dspace.lboro.ac.uk/2134/22915
Publisher Link: http://dx.doi.org/10.1016/j.ins.2016.09.004
ISSN: 0020-0255
Appears in Collections:Published Articles (Computer Science)
Published Articles (Aeronautical and Automotive Engineering)

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