A Light Field Image Quality Assessment Model Based on Symmetry and Depth Features

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

5 Scopus Citations
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Author(s)

  • Yu Tian
  • Huanqiang Zeng
  • Jing Chen
  • Jianqing Zhu
  • Kai-Kuang Ma

Related Research Unit(s)

Detail(s)

Original languageEnglish
Article number8979387
Pages (from-to)2046-2050
Journal / PublicationIEEE Transactions on Circuits and Systems for Video Technology
Volume31
Issue number5
Online published3 Feb 2020
Publication statusPublished - May 2021

Abstract

This letter presents a new full-reference image quality assessment (IQA) method for conducting the perceptual quality evaluation of the light field (LF) images, called the symmetry and depth feature-based model (SDFM). Specifically, the radial symmetry transform is first employed on the luminance components of the reference and distorted LF images to extract their symmetry features for capturing the spatial quality of each view of an LF image. Second, the depth feature extraction scheme is designed to explore the geometry information inherited in an LF image for modeling its LF structural consistency across views. The similarity measurements are subsequently conducted on the comparison of their symmetry and depth features separately, which are further combined to achieve the quality score for the distorted LF image. Note that the proposed SDFM that explores the symmetry and depth features is conformable to the human vision system, which identifies the objects by sensing their structures and geometries. Extensive simulation results on the dense light fields dataset have clearly shown that the proposed SDFM outperforms multiple classical and recently developed IQA algorithms on quality evaluation of the LF images.

Research Area(s)

  • Light field image, image quality assessment, symmetry feature, depth feature

Citation Format(s)

A Light Field Image Quality Assessment Model Based on Symmetry and Depth Features. / Tian, Yu; Zeng, Huanqiang; Hou, Junhui; Chen, Jing; Zhu, Jianqing; Ma, Kai-Kuang.

In: IEEE Transactions on Circuits and Systems for Video Technology, Vol. 31, No. 5, 8979387, 05.2021, p. 2046-2050.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review