Neurophysiological Assessment of Image Quality from EEG Using Persistent Homology of Brain Network

The neuropsychological characteristics inside the brain are still not sufficiently understood during the conventional image quality assessment procedure. In this paper, we extract the physiologically meaningful features of brain responses to different distortion levels images in conventional image assessment by combining persistent homology analysis with electroencephalogram (EEG). The experimental results show that more brain regions in the frontal lobe are involved when the subject perceives an unclear image compared to a clear one, which indicates that human perception of image quality might be related to the advanced cognitive processes to some extent. Meanwhile, a statistically significantly higher persistent entropy of EEG data evoked by a clear image compared to that of an unclear image is observed in several frequency bands. In general, this paper evaluates and quantifies quality-related neural correlates by persistent homology features of EEG signal, which provides an approach for a utility neurophysiological assessment of image quality.