Journal of Broadcast Engineering (방송공학회논문지)

The Korean Institute of Broadcast and Media Engineers (한국방송∙미디어공학회)
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Efficient Transform-Domain Noise Reduction for H.264 Video Encoding

H.264 동영상 부호화를 위한 효과적인 주파수 영역 잡음 제거

  • Published : 2009.07.30
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Abstract

This paper proposes an efficient transform-domain noise reduction scheme in an H.264 video encoder, where the generalized Wiener filtering is performed in a quantization process by multiplying each transform block with its adaptive multiplication factor. In practice, the computational complexity of the proposed scheme is negligible by replacing the multiplication operation with a simple look-up table method. Also, experimental results show that the proposed scheme provides outstanding noise reduction performance in an H.264 video encoder.

본 논문은 H.264 동영상 부호기를 위한 효율적인 주파수 영역 잡음 제거 기법을 제안한다. 각 변환 블록과 잡음 제거를 위해 변형된 곱셈 팩터 행렬를 내적하는 방식으로 Wiener filtering이 이루어진다. 구현 시 look-up table을 이용하면 제안한 방법에서의 곱셈 연산을 간단히 대신할 수 있기 때문에 필터링에 의한 연산량은 무시할 만하다. 또한, 실험 결과를 통해 제안한 방법이 H.264 부호기에서 두드러진 잡음 제거 성능을 보임을 알 수 있다.

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References

  1. K. J. Boo, and N. K. Bose, "A motion-compensated spatio-temporal filter for image sequences with signal-dependent noise," IEEE Trans. Circ. Syst. Video Technol., vol. 8, no. 3, pp. 287-298, 1998 https://doi.org/10.1109/76.678623
  2. S. W. Lee, V. Maik, J. Jang, J. Shin, and J. Paik, "Noise-adaptive spatio-temporal filter for real-time noise removal in low light level images," IEEE Trans. Consumer Electronics, vol. 51, no. 2, pp. 648-653, 2005 https://doi.org/10.1109/TCE.2005.1468014
  3. S. Yang, and T. Lu, "A practical design flow of noise reduction algorithm for video post processing," IEEE Trans. Consumer Electronics, vol. 53, no. 3, pp. 995-1002, 2007 https://doi.org/10.1109/TCE.2007.4341578
  4. G. de Haan et al., "Television noise reduction IC," IEEE Trans. Consumer Electronics, vol. 44, no. 1, pp. 143-153, 1998 https://doi.org/10.1109/30.663741
  5. N. Rajpoot, Z. Yao, and R. Wilson, “Adaptive wavelet restoration of noisy video sequences,” Proc. IEEE ICIP, pp.24-27, Lausanne, Switzerland, 2004 https://doi.org/10.1109/ICIP.2004.1419459
  6. S. Rahman, M. Ahmad, and M. Swamy, “Video de-noising based on inter-frame statistical modeling of wavelet coefficients,” IEEE Trans. Circ. Syst. Video Technol., vol. 17, no. 2, pp. 187-198, 2007 https://doi.org/10.1109/TCSVT.2006.887079
  7. A. K. Jain, Fundamentals of Digital Image Processing, Prentice-Hall, 1989
  8. S. D. Kim and J. B. Ra, "Efficient block-based video encoder embedding a Wiener filter for noisy video sequences," Journal of Visual Comm. Image Rep., vol. 14, no. 1, pp. 22-40, 2003 https://doi.org/10.1016/S1047-3203(02)00012-3
  9. G. Sullivan and H. Yu, "Joint draft 6 of new profiles for professional applications amendment to ITU-T Rec. H.264 & ISO/IEC 14496-10," ISO/IEC JTC1/SC29/WG11 and IUT-T SG16 Q.6 Document JVT-V204, Jan. 2007
  10. B. C. Song and K. W. Chun, "Noise power estimation for effective de-noising in a video encoder," IEEE International Conf. Acoustics, Speech, and Signal Process.(ICASSP), pp. II357-II360, Philadelphia, USA, March 2005
  11. W. Niehsen and M. Brunig, "Covariance analysis of motion-compensated frame differences," IEEE Trans. Circ. Syst. Video Technol., vol. 9, no. 4, pp. 536-539, 1999 https://doi.org/10.1109/76.767119
  12. VCODEX, "H.264/MPEG4 Part10: Transform & Quantization," www.vcodex.com, accessed 2007
  13. H.264/MPEG4 AVC reference software http://iphome.hhi.de/suehring/tml/, accessed 2007