DIBR-Synthesized Image Quality Assessment via Statistics of Edge Intensity and Orientation

DOI Web Site 参考文献17件
  • ZHOU Yu
    School of Information and Control Engineering, China University of Mining and Technology
  • LI Leida
    School of Information and Control Engineering, China University of Mining and Technology
  • GU Ke
    BJUT Faculty of Information Technology, Beijing University of Technology
  • LU Zhaolin
    School of Information and Control Engineering, China University of Mining and Technology
  • CHEN Beijing
    School of Computer and Software, Nanjing University of Information Science and Technology
  • TANG Lu
    School of Information and Control Engineering, China University of Mining and Technology

抄録

<p>Depth-image-based-rendering (DIBR) is a popular technique for view synthesis. The rendering process mainly introduces artifacts around edges, which leads to degraded quality. This letter proposes a DIBR-synthesized image quality metric by measuring the Statistics of both Edge Intensity and Orientation (SEIO). The Canny operator is first used to detect edges. Then the gradient maps are calculated, based on which the intensity and orientation of the edge pixels are computed for both the reference and synthesized images. The distance between the two intensity histograms and that between the two orientation histograms are computed. Finally, the two distances are pooled to obtain the overall quality score. Experimental results demonstrate the advantages of the presented method.</p>

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