NDLI: Stereoscopic image quality assessment by analysing visual hierarchical structures and binocular effects

Content Provider	IET Digital Library
Author	Ding, Yong Zhao, Yang Chen, Xiaodong Zhu, Xiaolei Andrey, Krylov
Abstract	In the design of three-dimensional image processing systems, stereoscopic image quality assessment (SIQA) plays an indispensable role as a performance evaluator and a supervisor, yet the study upon which remains immature due to the complexity of the human visual system (HVS). In this study, a novel SIQA method is proposed by extracting quality-aware image features according to the properties of the hierarchical structure in the HVS. Especially, the interests of the primary and secondary visual cortex are taken into consideration, so that the image quality representation is constructed in a way both accurate and efficient. Moreover, influences caused by binocular effects including binocular rivalry and binocular visual discomfort are accounted to further improve the performance of the proposed method. The superiority of the proposed method is validated through experiments on public databases in comparison to state-of-the-art works in terms of accuracy and robustness.
Starting Page	1608
Ending Page	1615
Page Count	8
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 10, Aug (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/10
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.5605
Journal	IET Image Processing
Publisher Date	2019-03-22
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Binocular Effects Binocular Visual Discomfort Computer Vision And Image Processing Technique Hierarchical Structure Human Visual System HVS Image Quality Representation Optical, Image And Video Signal Processing Primary Cortex Quality-aware Image Feature Secondary Visual Cortex SIQA Method Stereo Image Processing Stereoscopic Image Quality Assessment Three-dimensional Image Processing System Visual Hierarchical Structure Visual Perception
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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