Toward a neurophysiological measure of image quality perception based on algebraic topology analysis

The bandwidth of internet connections is still a bottleneck when transmitting large amounts of images, making the image quality assessment essential. Neurophysiological assessment of image quality has highlight advantages for it does not interfere with natural viewing behavior. However, in JPEG compression, the previous study is hard to tell the difference between the electroencephalogram (EEG) evoked by different quality images. In this paper, we propose an EEG analysis approach based on algebraic topology analysis, and the result shows that the difference between Euler characteristics of EEG evoked by different distortion images is striking both in the alpha and beta band. Moreover, we further discuss the relationship between the images and the EEG signals, and the results implied that the algebraic topological properties of images are consistent with that of brain perception, which is possible to give birth to brain-inspired image compression based on algebraic topological features. In general, an algebraic topology-based approach was proposed in this paper to analyze the perceptual characteristics of image quality, which will be beneficial to provide a reliable score for data compression in the network and improve the network transmission capacity.