Influence of significant target on image quality assessment via EEG The significant target in the image shows how much people pay attention to certain objects in the image when viewing the image. These significant targets will affect human perception of image quality when quality change occurs. But in recent years, most of the image quality perception research based on elsctroencephalography(EEG) were not considered of these significant targets. Therefore, this paper obtains the EEG signals of the subjects through an image rendering experiment for the presence or absence of significant targets, and compares the signal differences. The experimental results show that there is no significant effect on the image quality perception in the perceptible range. If there is a large degree of distortion, whether there is significant target has an important impact on the image quality perception.

Perceptual Image Quality Assessment: Recent Progress and Trends Image quality assessment (IQA) is useful in many visual processing systems but challenging to perform in line with the human perception. A great deal of recent research effort has been directed towards IQA. In order to overcome the difficulty and infeasibility of subjective tests in many situations, the aim of such effort is to assess visual quality objectively towards better alignment with the perception of the Human Visual system (HVS). In this work, we review and analyze the recent progress in the areas related to IQA, as well as giving our views whenever possible. Following the recent trends, we discuss the engineering approach in more details, explore the related aspects for feature pooling, and present a case study with machine learning.