Neural evidence for image quality perception based on algebraic topology

PLoS One. 2021 Dec 16;16(12):e0261223. doi: 10.1371/journal.pone.0261223. eCollection 2021.

Abstract

In this paper, the algebraic topological characteristics of brain networks composed of electroencephalogram(EEG) signals induced by different quality images were studied, and on that basis, a neurophysiological image quality assessment approach was proposed. Our approach acquired quality perception-related neural information via integrating the EEG collection with conventional image assessment procedures, and the physiologically meaningful brain responses to different distortion-level images were obtained by topological data analysis. According to the validation experiment results, statistically significant discrepancies of the algebraic topological characteristics of EEG data evoked by a clear image compared to that of an unclear image are observed in several frequency bands, especially in the beta band. Furthermore, the phase transition difference of brain network caused by JPEG compression is more significant, indicating that humans are more sensitive to JPEG compression other than Gaussian blur. In general, the algebraic topological characteristics of EEG signals evoked by distorted images were investigated in this paper, which contributes to the study of neurophysiological assessment of image quality.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Algorithms
  • Artifacts
  • Brain / diagnostic imaging
  • Brain / physiology
  • Electroencephalography / methods
  • Female
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Male
  • Models, Theoretical
  • Nerve Net / diagnostic imaging*
  • Nerve Net / physiology*
  • Perception

Associated data

  • Dryad/10.5061/dryad.bcc2fqzdj

Grants and funding

a) The Funding List: Key Research and Development Program of Zhejiang Province under Grant No.2019C03138 and No.2019C01002. b) The funders provided the experiment material and equipment for our study. c) The Key Research and Development Program of Zhejiang Province (Grant No.2019C03138 and No.2019C01002) provided a salary for Chang Liu, Dingguo Yu, and Xiaoyu Ma.