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Depth Up-Sampling via Pixel-Classifying and Joint Bilateral Filtering

  • Ren, Yannan (School of Information Science and Engineering, Shandong University) ;
  • Liu, Ju (School of Information Science and Engineering, Shandong University) ;
  • Yuan, Hui (School of Information Science and Engineering, Shandong University) ;
  • Xiao, Yifan (School of Information Science and Engineering, Shandong University)
  • Received : 2016.11.21
  • Accepted : 2018.02.05
  • Published : 2018.07.31

Abstract

In this paper, a depth image up-sampling method is put forward by using pixel classifying and jointed bilateral filtering. By analyzing the edge maps originated from the high-resolution color image and low-resolution depth map respectively, pixels in up-sampled depth maps can be classified into four categories: edge points, edge-neighbor points, texture points and smooth points. First, joint bilateral up-sampling (JBU) method is used to generate an initial up-sampling depth image. Then, for each pixel category, different refinement methods are employed to modify the initial up-sampling depth image. Experimental results show that the proposed algorithm can reduce the blurring artifact with lower bad pixel rate (BPR).

Keywords

References

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