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Benchmarking screen content image quality evaluation in spatial psychovisual modulation display system
Yuanchun Chen1; Yuanchun Chen1; Ke Gu2; Xinfeng Zhang3; Weisi Lin3; Jiantao Zhou4
2018-05-10
Conference NamePacific Rim Conference on Multimedia
Source PublicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10735 LNCS
Pages629-640
Conference Date28-29 September
Conference PlaceHarbin, China
Author of SourceSpringer Verlag
Abstract

Spatial Psychovisual Modulation (SPVM) is a novel information display technology which aims to simultaneously generate multiple visual percepts for different viewers on a single display. The SPVM system plays an important role in information security. In a SPVM system, the viewers wearing polarized glasses can see a specific image (called personal view), and meanwhile the viewers not wearing glasses can also see a semantically meaningful image (called shared view). Researches on screen content image (SCI) are very hot recently, which have received a great amount of attention from multiple fields in multimedia signal processing. In this paper, we focus our gaze on how the users’ quality-of-experience on SCIs is influenced under the SPVM display system. To this aim, we implement a comprehensive subjective quality assessment of SCIs by building a database which contains the distorted SCIs generated by a SPVM system. We run prevailing image quality methods on the newly established database, and results of experiments indicate that existing image quality metrics cannot reach a good performance, possibly due to some unique distortions, e.g. false contour and ghosting artifacts of SPVM-generated SCIs. Furthermore, we also point out some potential features which may lead to a high-performance metric by some appropriate modification and combination. © Springer International Publishing AG, part of Springer Nature 2018.

DOI10.1007/978-3-319-77380-3_60
Indexed ByCPCI-S
Language英語English
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Theory & Methods
WOS IDWOS:000460422000060
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Cited Times [WOS]:1   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Faculty of Science and Technology
Corresponding AuthorYuanchun Chen
Affiliation1.Institute of Image Communication and Information Processing, Shanghai Jiao Tong University, Shanghai, China;
2.BJUT Faculty of Information Technology, Beijing University of Technology, Beijing, China;
3.Nanyang Technological University, Singapore, Singapore;
4.University of Macau, China
Recommended Citation
GB/T 7714
Yuanchun Chen,Yuanchun Chen,Ke Gu,et al. Benchmarking screen content image quality evaluation in spatial psychovisual modulation display system[C]//Springer Verlag,2018:629-640.
APA Yuanchun Chen,Yuanchun Chen,Ke Gu,Xinfeng Zhang,Weisi Lin,&Jiantao Zhou.(2018).Benchmarking screen content image quality evaluation in spatial psychovisual modulation display system.Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),10735 LNCS,629-640.
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