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A Depth Video Coding In-Loop Median Filter Based on Joint Weighted Sparse Representation

A Depth Video Coding In-Loop Median Filter Based on Joint Weighted Sparse Representation
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摘要 The existing depth video coding algorithms are generally based on in-loop depth filters, whose performance are unstable and easily affected by the outliers. In this paper, we design a joint weighted sparse representation-based median filter as the in-loop filter in depth video codec. It constructs depth candidate set which contains relevant neighboring depth pixel based on depth and intensity similarity weighted sparse coding, then the median operation is performed on this set to select a neighboring depth pixel as the result of the filtering. The experimental results indicate that the depth bitrate is reduced by about 9% compared with anchor method. It is confirmed that the proposed method is more effective in reducing the required depth bitrates for a given synthesis quality level. The existing depth video coding algorithms are generally based on in-loop depth filters, whose performance are unstable and easily affected by the outliers. In this paper, we design a joint weighted sparse representation-based median filter as the in-loop filter in depth video codec. It constructs depth candidate set which contains relevant neighboring depth pixel based on depth and intensity similarity weighted sparse coding, then the median operation is performed on this set to select a neighboring depth pixel as the result of the filtering. The experimental results indicate that the depth bitrate is reduced by about 9% compared with anchor method. It is confirmed that the proposed method is more effective in reducing the required depth bitrates for a given synthesis quality level.
出处 《Wuhan University Journal of Natural Sciences》 CAS CSCD 2016年第4期351-357,共7页 武汉大学学报(自然科学英文版)
基金 Supported by the National Natural Science Foundation of China(61462048)
关键词 depth video coding virtual view synthesis joint weighted sparse representation depth video coding virtual view synthesis joint weighted sparse representation
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  • 1Smolic A, Mueller K, Merkle P. Multi-view Video plus Depth (MVD) Format for Advanced 3D Video Sys-tem[C]//23./ ISO/IEC JTC1/SC29/WG\ 1 and ITU-T SG\6, San Jose: ISO/IEC and ITU-T Press, 2007, 6: 21-27.
  • 2Woo S K, Antonio O. Depth map distortion analysis for view rendering and depth coding[C]//Prac International Conf Image Processing. Cairo: IEEE Press, 2009: 721-724.
  • 3ITU-T.MVC extension for inclusion of depth maps draft text 4(JCT3V-A1001) [S]. Geneva: ITU-TPress, 2012.
  • 4Hannuksela M, Rusanovskyy D, Su W, et al. Multiview-video-plus-depth coding based on the advanced video coding standard [J]. IEEE Trans Image Processing, 2013, 22(9): 3449-3458.
  • 5Kwan J O, Vetro A , Ho S Y. Depth coding using a boundary reconstruction filter for 3D video systems [J], IEEE Trans Circuits and Systems for Video Technology, 2011, 21(3): 350-359.
  • 6Liu S J, Lai P L. New depth coding techniques with utilization of corresponding video [J]. IEEE Trans Broadcasting, 2011,57 (2): 551-561.
  • 7Lim I, Lee J. Adaptive nonlocal range filter in depth map coding [C] // International Conf Image Processing. Florida: IEEE Press, 2012: 1285-1288.
  • 8Huang K, Aviyente S. Sparse Representation for Signal Classification [C] // Neural Information Processing Systems. Vancouver: MIT Press, 2006: 609-616.
  • 9Huang Y, Huang K Q. Salient Coding for Image Classification [C] // International Conf Computer Vision and Pattern Recognition. Colorado: IEEE Press, 2011: 1753-1760.
  • 10Wang J, Yang J, Yu K, et al. Locality-constrained Linear Coding for Image Classification [C] // International Conf. Computer Vision and Pattern Recognition. San Francisco: IEEE Press, 2010: 3360-3367.

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