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Asymmetric Foveated Just-Noticeable-Difference Model for Images With Visual Field Inhomogeneities.

Authors :
Chen, Zhenzhong
Wu, Wei
Source :
IEEE Transactions on Circuits & Systems for Video Technology. Nov2020, Vol. 30 Issue 11, p4064-4074. 11p.
Publication Year :
2020

Abstract

Just noticeable difference (JND) models reveal visibility limitation of human visual system (HVS) and exploit perceptual redundancy in the visual signal. Conventional just noticeable difference (JND) model supposes the visual acuity is homogeneous with or without considerations on the isoeccentric locations. Recent research on vision science indicates that the effect of eccentricity on visual sensitivity is not homogeneous across the visual field (VF). Relevant studies have found visual acuity at the isoeccentric locations is better along the horizontal meridian than along the vertical meridian, i.e., horizontal-vertical anisotropy (HVA). Along the vertical meridian, better performance has been reported for the inferior meridian compared to the superior meridian, i.e., vertical-meridian asymmetry (VMA). These properties of HVS should be taken into account to yield a better JND estimation, for better exploiting the perceptual redundancy. In this paper, we use two hemi-ellipses to represent the iso-acuity contour, which can better express the HVA and VMA effects. Moreover, we design psychophysical experiments under different test conditions, where the results show the hemi-ellipse model performs better when compared to the circular model. Finally, we build an asymmetric foveated JND model using two hemi-ellipses for approximation. When comparing with traditional JND models, experimental results demonstrate the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10518215
Volume :
30
Issue :
11
Database :
Academic Search Index
Journal :
IEEE Transactions on Circuits & Systems for Video Technology
Publication Type :
Academic Journal
Accession number :
146783109
Full Text :
https://doi.org/10.1109/TCSVT.2019.2952675