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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
Scopus ID2-s2.0-85047445051
Fulltext Access
Citation statistics
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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