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.
Original language | English |
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Article number | 7902111 |
Pages (from-to) | 1694-1706 |
Number of pages | 13 |
Journal | IEEE Transactions on Circuits and Systems for Video Technology |
Volume | 28 |
Issue number | 8 |
DOIs | |
Publication status | Published - 2018 Aug |
Keywords
- EEG
- MOS
- SSVEP
- classification
- spatio-spectral decomposition
- video quality assessment
ASJC Scopus subject areas
- Media Technology
- Electrical and Electronic Engineering