Journal of the Institute of Electronics Engineers of Korea SP (대한전자공학회논문지SP)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Motion Adaptive Temporal-Spatial Noise Reduction Scheme with Separated Pre- and Post-Spatial Filter

분리된 전처리 및 후처리 광간영역 필터를 가진 움직임 적응적 시공간영역 잡음 제거 기법

  • 김성득 (안동대학교 정보전자공학교육과) ;
  • 임경원 ((주) LG전자 DTV연구소)
  • Published : 2009.09.25
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Abstract

A motion adaptive video noise reduction scheme is proposed by cascading a temporal filter and a spatial filter. After a noise-robust motion detection is performed with a pre-spatial filter, the strength of the motion adaptive temporal filter is controlled by the amount of temporal movement. In order to fully utilize the temporal correlation of video signal, noisy input image is processed first by the temporal filter, therefore, image details of temporally stationary region are quite well preserved while undesired noises are suppressed. In contrast to the pre-spatial filter used for the robust motion detection, the cascaded post-spatial filter removes the remained noises by considering the strength of the temporal filter and the spatial self-similarity search results obtained from the pre-spatial filter.

시간영역 필터와 공간영역 필터를 연결한 움직임 적응적 동영상 잡음 제거기법을 제안한다. 움직임 적응적 시간영역 필터에서는 전처리 공간영역 필터를 활용하여 잡음에 강인한 움직임 검출을 수행하고, 움직임의 양에 따라 적응적으로 필터링 강도를 조절한다. 동영상에 내재된 시간적 연관성을 충분히 활용하기 위해, 잡음이 있는 입력 영상은 시간영역 필터에 의해 처음으로 처리된다. 따라서 시간적 연관성이 큰 동영상에서, 영상의 세밀한 부분을 잘 보존하며 잡음을 제거할 수 있다. 움직임 검출을 위해 사용되는 전처리 공간영역 필터와는 다르게, 후처리 공간영역 필터는 시간영역 필터의 강도와 전처리 공간영역 필터에서 얻어진 공간영역 자기유사성 탐색 결과를 바탕으로 공간영역 필터링을 수행한다.

Keywords

References

  1. J. S. Lim, "Two-dimensional signal and image processing," Prentice-Hall, 1990
  2. G. de Haan, T. G. Kwaaitaal-Spassova, and O. A. Ojo, "Automatic 2-D and 3-D noise filtering for television receivers," Proc. Int. Workshop HDTV '94, Oct. 1994
  3. G. de Haan, T. G. Kwaaitaal-Spassova, M. Larragy, and O. A. Ojo, "Memory integrated noise reduction IC for television," IEEE Trans. Consumer Electronics, vol. 42. no. 2, pp. 175-181, May 1996 https://doi.org/10.1109/30.494418
  4. M. Ghazal, A. Amer, and A. Ghrayeb, "Homogeneity-based directional sigma filtering of video noise," Proc. Int. Conf. Image Processing (ICIP), vol.1, pp. 97-100, Sept. 2005
  5. G. Ramponi, "The rational filter for image smoothing," IEEE Signal Processing Letters, vol. 3, no. 3, pp. 63-65, March 1996 https://doi.org/10.1109/97.481156
  6. C. Tomasi and R. Manduchi, "Bilateral filtering for gray and color images," Proc. International Conference Computer Vision (ICCV), pp. 839-846, Jan. 1998 https://doi.org/10.1109/ICCV.1998.710815
  7. A. Buades, B. Coll, and J.-M. Morel, "A non-local algorithm for image denoising," Computer Vision and Pattern Recognition (CVPR), vol. 2, pp. 60-65, June 2005
  8. D. Tschumperle. "Fast anisotropic smoothing of multi-valued images using curvature-preserving PDE's," International Journal of Computer Vision (IJCV), vol. 68, no. 1, pp. 65-82, June 2006 https://doi.org/10.1007/s11263-006-5631-z
  9. A. C. Kokaram, "Motion picture restoration," Ph.D thesis, Cambridge University Engineering Department, May 1993.
  10. S. D. Kim and J. B. Ra, "Efficient block-based video encoder embedding a Wiener filter for noisy video sequences," Journal of Visual Communication and Image Representation, vol. 14, pp. 22-40, March 2003 https://doi.org/10.1016/S1047-3203(02)00012-3
  11. E. Dubois and S. Sabri, "Noise reduction in image sequences using motion-compensated temporal filtering," IEEE Trans. Communications, vol. COM-32, no. 7, pp. 826-832, July 1984