Distributed video coding with 3D recursive search block matching

This paper presents a novel video compression system with a low complexity encoder. Based on the Slepian-Wolf theorem and the Wyner-Ziv theorem, a video is intraframe coded and interframe decoded in this system. The system performance, the compression rate and the video quality, is affected by the difference between the source information and the side information. To increase the accuracy of the side information, a modified three dimensional recursive search block matching is proposed. The resulting motion vectors preserve the true motion of objects because of the spatial and temporal consistency. The results obtained show a significant improvement over full search block matching algorithm in the term of the rate-distortion measure. The different quantizer design and puncturing table reduce the necessary parity bits for the decoding, and also increase the PSNR. The system performance is also much closer to H.263 interframe coding

[1]  Kannan Ramchandran,et al.  Distributed code constructions for the entire Slepian-Wolf rate region for arbitrarily correlated sources , 2004, Data Compression Conference, 2004. Proceedings. DCC 2004.

[2]  R. A. McDonald,et al.  Noiseless Coding of Correlated Information Sources , 1973 .

[3]  Jack K. Wolf,et al.  Noiseless coding of correlated information sources , 1973, IEEE Trans. Inf. Theory.

[4]  Aaron D. Wyner,et al.  The rate-distortion function for source coding with side information at the decoder , 1976, IEEE Trans. Inf. Theory.

[5]  Bernd Girod,et al.  Distributed Video Coding , 2005, Proceedings of the IEEE.

[6]  Gerard de Haan,et al.  True-motion estimation with 3-D recursive search block matching , 1993, IEEE Trans. Circuits Syst. Video Technol..

[7]  Bernd Girod,et al.  Compression with side information using turbo codes , 2002, Proceedings DCC 2002. Data Compression Conference.

[8]  Ying Zhao,et al.  Compression of binary memoryless sources using punctured turbo codes , 2002, IEEE Communications Letters.

[9]  Zixiang Xiong,et al.  Distributed source coding for sensor networks , 2004, IEEE Signal Processing Magazine.