Light Field Image Quality Assessment via the Light Field Coherence

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

View graph of relations


  • Yu Tian
  • Huanqiang Zeng
  • Junhui Hou
  • Jing Chen
  • Kai-kuang Ma

Related Research Unit(s)


Original languageEnglish
Journal / PublicationIEEE Transactions on Image Processing
Publication statusOnline published - 17 Jul 2020


In this paper, a novel full-reference image quality assessment (IQA) method for evaluating the quality of the distorted light field (LF) image against its reference LF image is proposed, called the log-Gabor feature-based light field coherence (LGF-LFC). Based on the fact that to compare two LF images, it essentially boils down to measure how coherent of these two LF images, we attempt to measure the degree of their LF coherence (LFC). To pursue this goal, the salient features from the reference and distorted LF images under comparison need to be extracted. By considering that the Gabor feature has the ability to well characterize the human visual system (HVS) perception, and the special characteristics of the LF images, the multi-scale and single-scale Gabor feature extraction schemes are developed to extract the multi-scale log-Gabor features from the sub-aperture images (SAIs) and the single-scale log-Gabor feature from the epi-polar images (EPIs), respectively. Note that the former can reflect the image details (via the SAIs), while the latter indicates the viewing consistency (via the EPI’s depth information). The similarity measurements are subsequently conducted on the comparison of their SAIs and that of their EPIs separately, followed by combining them together for arriving at the final score. Extensive simulation results have clearly demonstrated that the proposed LGF-LFC is more consistent with the perception of the HVS on the quality evaluation of the LF images than multiple classical and state-of-the-art IQA methods.

Research Area(s)

  • Light field image, light field coherence, subaperture image, epi-polar plane image, image quality assessment