Blind quality assessment for 3D synthesised video with binocular asymmetric distortion. Issue 6 (1st April 2020)

• Record Type: Journal Article
• Authors: Cui, Shuainan; Peng, Zongju; Chen, Fen; Zou, Wenhui; Jiang, Gangyi; Yu, Mei
• Is Part Of: IET image processing. Volume 14:Issue 6(2020)
• Page Start: 1027
• Page End: 1034
• Publication Date: 2020-04-01
• Subjects: rendering (computer graphics) -- video signal processing -- statistical analysis -- image texture -- distortion -- cameras; binocular asymmetric distortion -- blind quality assessment method -- 3D synthesised video -- local edge deformations -- objective quality score -- texture information -- asymmetry 3D‐SV database; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2019.1085
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : During the process of watching 3D synthesised video (3D‐SV) and switching viewpoints, there is a case of asymmetric distortion, the left(right) viewpoint is a synthesised video generated by rendering technique, and the right(left) viewpoint is a real video taken by the camera. How to accurately estimate the quality of 3D‐SV with binocular asymmetric distortions is a new and challenging problem. Aiming at this problem, a blind quality assessment method for 3D‐SV with binocular asymmetric distortions is proposed. Firstly, the local edge deformations of synthesised videos at different scales are measured by calculating their standard deviations. Secondly, the global naturalness of synthesised videos is computed by analysing their natural statistical characteristics. Thirdly, a strategy for fusing left and right quality scores is proposed, which considers their texture information in different directions. Finally, the random forest is used to obtain an objective quality score. The experimental results show the superiority of the proposed method on asymmetry 3D‐SV database.