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Assessing Perceived Image Quality Using Steady-State Visual Evoked Potentials and Spatio-Spectral Decomposition

Authors
Bosse, SebastianAcqualagna, LauraSamek, WojciechPorbadnigk, Anne K.Curio, GabrielBlankertz, BenjaminMueller, Klaus-RobertWiegand, Thomas
Issue Date
8월-2018
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
EEG; SSVEP; video quality assessment; classification; MOS; spatio-spectral decomposition
Citation
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, v.28, no.8, pp.1694 - 1706
Indexed
SCIE
SCOPUS
Journal Title
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
Volume
28
Number
8
Start Page
1694
End Page
1706
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/74231
DOI
10.1109/TCSVT.2017.2694807
ISSN
1051-8215
Abstract
Steady-state visual evoked potentials (SSVEPs) are neural responses, measurable using electroencephalography (EEG), that are directly linked to sensory processing of visual stimuli. In this paper, SSVEP is used to assess the perceived quality of texture images. The EEG-based assessment method is compared with conventional methods, and recorded EEG data are correlated to obtained mean opinion scores (MOSs). A dimensionality reduction technique for EEG data called spatio-spectral decomposition (SSD) is adapted for the SSVEP framework and used to extract physiologically meaningful and plausible neural components from the EEG recordings. It is shown that the use of SSD not only increases the correlation between neural features and MOS to r = -0.93, but also solves the problem of channel selection in an EEG-based image-quality assessment.
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