View-spatial-temporal post-refinement for view synthesis in 3D video systems

Linwei ZHU, Yun ZHANG, Mei YU, Gangyi JIANG, Sam KWONG

Research output: Journal PublicationsJournal Article (refereed)peer-review

10 Citations (Scopus)


Depth image based rendering is one of key techniques to realize view synthesis for three-dimensional television and free-viewpoint television, which provide high quality and immersive experiences to end viewers. However, artifacts of rendered images, including holes caused by occlusion/disclosure and boundary artifacts, may degrade the subjective and objective image quality. To handle these problems and improve the quality of rendered images, we present a novel view-spatial-temporal post-refinement method for view synthesis, in which new hole-filling and boundary artifact removal techniques are proposed. In addition, we propose an optimal reference frame selection algorithm for a better trade-off between the computational complexity and rendered image quality. Experimental results show that the proposed method can achieve a peak signal-to-noise ratio gain of 0.94 dB on average for multiview video test sequences when compared with the benchmark view synthesis reference software. In addition, the subjective quality of the rendered image is also improved. © 2013 Elsevier B.V.
Original languageEnglish
Pages (from-to)1342-1357
JournalSignal Processing: Image Communication
Issue number10
Early online date29 Aug 2013
Publication statusPublished - Nov 2013
Externally publishedYes

Bibliographical note

Thanks to Microsoft Research, HHI, Nagoya University and Poznan University of technology for providing multiview video sequence with fine quality depth information and camera parameters. This work was supported by National Natural Science Foundation of China under Grants 61102088, 61111140392 and 61271270, and in party by Guangdong Provincial Natural Science Foundation under Grant S2012010008457, Shenzhen Emerging Industries of the Strategic Basic Research Grant under Grant JCYJ20120617151719115, and the Innovation Fund Project for Graduate Student of Zhejiang Province ( YK2010047 ).


  • Boundary artifact
  • Depth image based rendering
  • Hole-filling
  • Multiview video
  • View synthesis


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