Journal of Broadcast Engineering (방송공학회논문지)

The Korean Institute of Broadcast and Media Engineers (한국방송∙미디어공학회)
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A PDWZ Encoder Using Code Conversion and Bit Interleaver

코드변환과 비트 인터리버를 이용한 화소영역 Wyner-Ziv 부호화 기법

  • Kim, Jin-Soo (School of Information Communications and Computer Engineering, Hanbat National University) ;
  • Kim, Jae-Gon (School of Electronics, Telecommunication & Computer Engineering, Korea Aerospace University) ;
  • Seo, Kwang-Deok (Computer & Telecommunications Engineering Division, Yonsei University)
  • 김진수 (한밭대학교 정보통신컴퓨터공학부) ;
  • 김재곤 (한국항공대학교 항공전자 및 정보통신공학부) ;
  • 서광덕 (연세대학교 컴퓨터정보통신공학부)
  • Published : 2010.01.30
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Abstract

Recently, DVC (Distributed Video Coding) is attracting a lot of research works since this enables us to implement a light-weight video encoder by distributing the high complex tasks such as motion estimation into the decoder side. In order to improve the coding efficiency of the DVC, the existing works have been focused on the efficient generation of side information (SI) or the virtual channel modeling which can describe the statistical channel noise well. But, in order to improve the overall performance, this paper proposes a new scheme that can be implemented with simple bit operations without introducing complex operation. That is, the performance of the proposed scheme is enhanced by using the fact that the Wyner-Ziv (WZ) frame and side information are highly correlated, and by reducing the effect of virtual channel noise which tends to be clustered in some regions. For this aim, this paper proposes an efficient pixel-domain WZ (PDWZ) CODEC which effectively exploits the statistical redundancy by using the code conversion and Gray code, and then reduces the channel noise by using the bit interleaver. Through computer simulations, it is shown that the proposed scheme can improve the performance up to 0.5 dB in objective visual quality.

분산 비디오 부호화(DVC: Distributed Video Coding)는 움직임 추정과 같은 복잡한 연산을 복호기측에서 처리함으로써 경량화 된 영상 부호화를 가능하게 하는 기술로 최근 많은 연구가 진행되고 있다. 분산 비디오 부호화의 부호화 성능을 개선하기 위한 기존의 연구는 주로 우수한 보조정보(SI: Side Information) 생성 또는 채널 특성을 잘 기술할 수 있는 채널 잡음 모델링에 집중되었다. 본 논문에서는 화소영역 Wyner-Ziv(Pixel Domain WZ: PDWZ) 코덱의 성능을 개선하기 위해 부호기에서 높은 복잡도를 도입하지 않고 간단한 비트 연산을 통하여 구현될 수 있는 성능 개선 방법을 제안한다. 즉, WZ 프레임과 보조정보 간에 존재하는 높은 상관성을 이용하고, 특정 영역에 집중하여 나타나는 가상채널 잡음을 줄임으로써 부호화 성능을 개선하는 방식을 제안한다. 이를 위해, 본 논문에서는 코드할당 및 그레이코드(Gray Code)를 사용하여 통계적 중복성을 효과적으로 이용하고, 더불어 비트 인터리버를 통하여 가상 채널 잡음의 영향을 줄이는 PDWZ 코덱을 제안한다. 모의실험을 통하여 제안한 방법은 최대 약 0.5 dB의 화질 개선을 제공할 수 있음을 보인다.

Keywords

References

  1. D. Slepian and J. Wolf, "Noiseless Coding of Correlated Information Sources," IEEE Trans. Information Theory, vol IT-19, no. 4, pp. 471-480, July 1973.
  2. A. Wyner and J. Ziv, "The Rate-distortion Function for Source Coding with Side Information at the Decoder," IEEE Trans. Information Theory, vol 22, pp. 1-10, Jan. 1976. https://doi.org/10.1109/TIT.1976.1055508
  3. B. Girod, A. Aaron, S. Rane and D. Rebollo-Monedero, "Distributed Video Coding," Proceedings of the IEEE, vol. 93, no. 1, pp. 71-83, Jan. 2005. https://doi.org/10.1109/JPROC.2004.839619
  4. R. Puri and K. Ramchandran, "PRISM: A "Reversed" Multimedia Coding Paradigm," in Proc. IEEE Int. Conf. on Image Processing, Barcelona, Spain, Sept. 2003.
  5. A. Aaron, R. Zhang, and B. Girod, "Wyner-Ziv Coding for Motion Video," in Proc. Asilomar Conference on Signals, Systems and Computers, Pacific Grove, USA, Nov. 2002.
  6. C. Brites, J. Ascenso, F. Pereira, "Studying Temporal Correlation Noise Modeling for Pixel Based Wyner-Ziv Video Coding," in Proc. IEEE Int. Conf. on Image Processing, pp.273-276, Oct 2006.
  7. L. Qing, X. He, R. Lv, "Modeling Non-stationary Correlation Noise Statistics for Wyner-Ziv Video Coding," in Proc. ICWAPR '07, vol. 1, Nov. 2007, pp. 316-320.
  8. Y. Li, S. Ma, D. Zhao, W. Gao, "Modeling Correlation Noise Statistics at Decoder for Multi-view Distributed Video Coding," in Proc. ISCAS 2009, May 2009, pp. 2597-2600.
  9. C. Brites, Pereira, F., "Correlation Noise Modeling for Efficient Pixel and Transform Domain Wyner–Ziv Video Coding," IEEE Trans. Circuits and Systems, vol. 18, no. 9, Sept. 2008, pp. 1177-1190.
  10. X. Huang, S. Forchhammer, "Improved Virtual Channel Noise Model for Transform Domain Wyner-Ziv Video Coding," in Proc. ICASSP 2009, April 2009, pp. 921-924.
  11. 고봉혁, 심혁재, 전병우, "복호 신뢰도에 기반하여 점진적으로 보조정보를 향상시키는 변환영역 Wyner-Ziv 부호화 방법," 방송공학회 논문지, 제13권 제6호, 2008년 11월, pp.892-904. https://doi.org/10.5909/JBE.2008.13.6.892
  12. 박천호, 심혁재, 전병우, "잡음 모델 선택을 이용한 Wyner-Ziv 비디오 압축," 전자공학회 논문지, 제46권, 제4호, 2009년 7월, pp.445-453.
  13. D. Mukherjee, B. Macchiavello and R. Queiroz, "A Simple Reversed-Complexity Wyner-Ziv Video Coding Mode Based on a Spatial Reduction Framework," in Proc. of SPIE Visual Com. and Img., vol.6508, pp.1Y1-1Y12, Jan 2007.
  14. D. Chen, D. Varodayan, M. Flierl, B. Girod, "Wyner-Ziv Coding of Multiview Images with Unsupervised Learning of Disparity and Gray Code," in Proc. IEEE Int. Conf. on Image Processing, San Diego, California, Oct. 2008.
  15. N. Anatrasirichai, D. Agrafiotis, M. Ouaret, F. Dufaux, T. Ebrahimi, "Performance Evaluation of Two State of the Art DVC Codecs," in Proc. ICDSC 2009, Aug. 2009.
  16. Z. Li, L. Liu and E. J. Delp, "Rate-distortion Analysis of Motion Side Estimation in Wyner-Ziv Video Coding," IEEE Trans. on Image Processing, vol. 16, no. 1, pp. 98-113, Jan. 2007. https://doi.org/10.1109/TIP.2006.884934
  17. E. Peixoto, R. L. Queiroz and D. Mukherjee, "On Side Information Generation for Wyner-Ziv Video Coding," in Proc. of Simposio Brasileiro de Tel., Rio de Janeiro, Brazil, Sept. 2008.
  18. J-s Kim, J-G Kim, K-d Seo, "A Side Information Generation Using Adaptive Estimation and Its Performance Comparison in PDWZ CODEC," to be appeared in J. of the Korea Institute of Maritime Info. & Comm. Sci., April 2010. https://doi.org/10.6109/jkiice.2010.14.2.383

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