A Reduced Complexity Post Filter to Simultaneously Reduce Blocking and Ringing Artifacts of Compressed Video Sequence

압축동영상의 블록화 및 링 현상 제거를 위한 저 계산량 Post필터

  • Hong, Min-Cheol (Dept.of Information Communication Electronics Engineering, Soongsil University) ;
  • Cha, Hyeong-Tae (Dept.of Information Communication Electronics Engineering, Soongsil University) ;
  • Han, Heon-Su (Dept.of Information Communication Electronics Engineering, Soongsil University)
  • 홍민철 (숭실대학교 정보통신전자공학부) ;
  • 차형태 (숭실대학교 정보통신전자공학부) ;
  • 한헌수 (숭실대학교 정보통신전자공학부)
  • Published : 2001.11.01

Abstract

In this paper, a reduced complexity fillet to simultaneously suppress the blocking and ringing artifacts of compressed video sequence is addressed. A new one dimensional regularized function to incorporate the smoothness to its neighboring pixels into the solution is defined, resulting in very low complexity filter The proposed regularization function consists of two sub-functions that combine local data fidelity and local smoothing constraints. The regularization parameters to control the trade-off between the local fidelity to the data and the smoothness are determined by available overhead information in decoder, such as maroc-block type and quantization step size. In addition, the regularization parameters are designed to have the limited range and stored as look-up-table, and therefore, the computational cost to determine the parameters can be reduced. The experimental results show the capability and efficiency of the proposed algorithm.

본 논문에서는 압축 동 영상의 블록화 및 링 현상을 동시에 제거 할 수 있는 저 계산량의 효율적인 필터방식을 제안한다. 인접 화소와의 상관 관계를 고려한 새로운 1차원 정규화 함수를 정의하여 기존의 정규화 복원 방식이 갖고 있던 계산량의 부하 문제를 해결하였다. 제안된 1차원 정규화 함수는 처리하고자 하는 화 소의 두 인접 화소를 이용한 2개의 부가 함수로 구성되어 있으며, 각각의 정규화 매개 변수는 복호화부에서 이용 가능한 매크로 블록의 타입 및 양자화 스텝 크기 등의 부가 정보를 이용하여 예측한다. 더불어, 본 논문에서는 정규화 매개 변수를 룩업 테이블 (look-up table)로 구성할 수 있도록 정규화 매개 변수의 영역을 제한하여 계산량을 더욱 줄일 수 있도록 구성하였다. 제안된 방식의 효율성을 실험 결과를 통해 확인할 수 있었다.

Keywords

References

  1. V. Bhaskaran and K. Konstantinides, Image and Video Compression Standards: Algorithm and Architectures, Kluwer Academic Publishers, 1995
  2. ITU-T SG16/Q15, 'ITU-T Draft H.263,' Jan. 1998
  3. ISO/IEC JTC1/SC29/WG11, 'MPEG4 Verification Model,' Oct, 1997
  4. B. Ramamurthi and A. Gersho, 'Nonlinear Space-Invariant Post Processing of Block Coded Images,' IEEE Trans. On ASSP, vol. ASSP-24, pp. 1258-1268, Oct. 1986
  5. S. D. Kim, J. Yi, H. M. Kim, and J. B. Ra, 'A Deblocking Filter with Two Separable Mode in Block Based Video Coding,' IEEE Trans. on Circuits and Systems for Video Technology, vol. 9, pp. 156-160, Feb. 1999 https://doi.org/10.1109/76.744282
  6. M.-C. Hong, C. M. Yon, and Y. M. Park, 'An Efficient Real Time Algorithm to Simultaneously Reduce Blocking and Ringing Artifacts of Compressed Video,' IEEE Proceeding cf ICIP, vol II, pp. 899-903, Oct. 1999 https://doi.org/10.1109/ICIP.1999.823028
  7. R. Rosenholtz and A. Zakhor, 'Iterative Procedure for Reducing of Blocking Effects in Transform Image Coding,' IEEE Trans. on Circuits and Systems for Video Technology, vol. 2, pp. 91-94, Mar. 1992 https://doi.org/10.1109/76.134377
  8. R. L. Stevenson, 'Reduction of Coding Artifacts in Transform Image Coding,' IEEE Proc. of Int' Conf. Acoust, Speech, and Signal Processing, pp. 401-404, 1993 https://doi.org/10.1109/ICASSP.1993.319832
  9. Y. Yang, N. P. Galatsanos, and A. K. Katsaggelos, 'Regularized Image Reconstruction from Imcomplete Block Discrete Cosine Transform Compressed Images,' IEEE Trans. on Circuits and Systems for Video Technology, vol. 3, pp. 421-432, Dec. 1993 https://doi.org/10.1109/76.260198
  10. H. C. Andrews and B. R. Hunt, Digital Image Restoration, Englewood Cliffs, rentice-Hall, 1977
  11. A. K. Katsaggelos, 'Iterative Image Restoration Algorithms,' Optical Engineering, vol. 28, pp. 735-748, July 1989
  12. M. R. Banham and A. K. Katsaggelos, 'Digital Image Restoration,' IEEE Signal Processing Magazine, vol. 14, pp. 24-41, Mar. 1997
  13. M.-C. Hong, Adaptive Regularized Image and Video Restoration, Ph.D Thesis, Northwestern University, Dept of ECE., Dec. 1997
  14. N. P. Galatsanos and A. K. Katsaggelos, 'Method for Choosing the Regularization Parameter and Estimating the Noise Variance in Image Restoration and Their Relationship,' IEEE Trans. on Image Processing, vol. 1, pp. 322-336, July 1992 https://doi.org/10.1109/83.148606
  15. IEEE Trans. on Image Processing v.1 Method for Choosing the Regularization Parameter and Estimating the Noise Variance in Image Restoration and Their Relationship N.P.Galatsanos;A.K.Katsaggelos