KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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Side Information Extrapolation Using Motion-aligned Auto Regressive Model for Compressed Sensing based Wyner-Ziv Codec

  • Li, Ran (Jiangsu Province Key Lab on Image Processing & Image Communication, Nanjing University of Posts and Telecommunications) ;
  • Gan, Zongliang (Jiangsu Province Key Lab on Image Processing & Image Communication, Nanjing University of Posts and Telecommunications) ;
  • Cui, Ziguan (Jiangsu Province Key Lab on Image Processing & Image Communication, Nanjing University of Posts and Telecommunications) ;
  • Wu, Minghu (Jiangsu Province Key Lab on Image Processing & Image Communication, Nanjing University of Posts and Telecommunications) ;
  • Zhu, Xiuchang (Jiangsu Province Key Lab on Image Processing & Image Communication, Nanjing University of Posts and Telecommunications)
  • Received : 2012.11.28
  • Accepted : 2013.02.06
  • Published : 2013.02.28
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Abstract

In this paper, we propose a compressed sensing (CS) based Wyner-Ziv (WZ) codec using motion-aligned auto regressive model (MAAR) based side information (SI) extrapolation to improve the compression performance of low-delay distributed video coding (DVC). In the CS based WZ codec, the WZ frame is divided into small blocks and CS measurements of each block are acquired at the encoder, and a specific CS reconstruction algorithm is proposed to correct errors in the SI using CS measurements at the decoder. In order to generate high quality SI, a MAAR model is introduced to improve the inaccurate motion field in auto regressive (AR) model, and the Tikhonov regularization on MAAR coefficients and overlapped block based interpolation are performed to reduce block effects and errors from over-fitting. Simulation experiments show that our proposed CS based WZ codec associated with MAAR based SI generation achieves better results compared to other SI extrapolation methods.

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References

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