방송공학회논문지 (Journal of Broadcast Engineering)

  • 제14권4호
  • /
  • Pages.501-508
  • /
  • 2009
  • /
  • 1226-7953(pISSN)
  • /
  • 2287-9137(eISSN)
한국방송∙미디어공학회 (The Korean Institute of Broadcast and Media Engineers)
권호 표지
DOI QR코드

DOI QR Code

H.264 동영상 부호화를 위한 효과적인 주파수 영역 잡음 제거

Efficient Transform-Domain Noise Reduction for H.264 Video Encoding

  • 발행 : 2009.07.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

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.

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.

키워드

참고문헌

  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