Advertisement

Computationally Efficient MCTF for MC-EZBC Scalable Video Coding Framework

  • A. K. Karunakar
  • M. M. Manohara Pai
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4815)

Abstract

The discrete wavelet transforms (DWTs) applied temporally under motion compensation (i.e. Motion Compensation Temporal Filtering (MCTF)) has recently become a very powerful tool in scalable video compression, especially when implemented through lifting. The major bottleneck for speed of the encoder is the computational complexity of the bidirectional motion estimation in MCTF. This paper proposes a novel predictive technique to reduce the computational complexity of MCTF. In the proposed technique the temporal filtering is done without motion compensation. The resultant high frequency frames are used to predict the blocks under motion. Motion estimation is carried out only for the predicted blocks under motion. This significantly reduces the number of blocks that undergoes motion estimation and hence the computationally complexity of MCTF is reduced by 44% to 92% over variety of standard test sequences without compromising the quality of the decoded video. The proposed algorithm is implemented in MC-EZBC, a 3D-subband scalable video coding system.

Keywords

Motion Estimation Motion Compensated Temporal Filtering Temporal Filtering MC-EZBC 

References

  1. 1.
    Taubman, D., Zakhor, A.: Multirate 3-D subband coding of video. IEEE Trans. Image Process. 3, 572–588 (1994)CrossRefGoogle Scholar
  2. 2.
    Wang, A., Xiong, Z., Chou, P., Mehrotra, S.: Three-dimensional wavelet coding of video with global motion compensation. In: Proc. Data Compression Conference, pp. 404–413 (March 1999)Google Scholar
  3. 3.
    Ohm, J.: Three-dimensional subband coding with motion compensation. IEEE Trans. Image Process. 3, 559–571 (1994)CrossRefGoogle Scholar
  4. 4.
    Choi, S., Woods, J.: Motion compensated 3d subband coding of video. IEEE Trans. Image Proc. 8, 155–167 (1999)CrossRefGoogle Scholar
  5. 5.
    Pesquet-Popescu, B., Bottreau, V.: Three dimensional lifting schemes for motion compensated video compression. In: IEEE Int. Conf. Accoust. Speech and Signal Proc., pp. 1793–1796 (2001)Google Scholar
  6. 6.
    Bottreau, V., Benetiere, M., Felts, B., Pesquet-Popescu, B.: A fully SCalable 3d subband video codec. In: IEEE Int. Conf. Image Proc., pp. 1017–1020 (2001)Google Scholar
  7. 7.
    Luo, L., Li, J., Li, S., Zhuang, Z., Zhang, Y.-Q.: Motion compensated lifting wavelet and its application in video coding. In: IEEE, Int. Conf. on Multimedia and Expo, pp. 481–484 (2001)Google Scholar
  8. 8.
    Secker, A., Taubman, D.: Motion-compensated highly scalable video compression using an adaptive 3d wavelet transform based on lifting. In: IEEE Int. conf. Image Proc., pp. 1029–1032 (2001)Google Scholar
  9. 9.
    Secker, A., Taubman, D.: Highly scalable video compression using a lifting-based 3d wavelet transform with deformable mesh motion compensation. In: IEEE Int. conf. Image Proc., pp. 749–752 (2002)Google Scholar
  10. 10.
    Secker, A., Taubman, D.: Lifting based invertible motion adaptive transform (LIMAT) framework for highly scalable video compression. IEEE Trans. Image Proc. 12, 1530–1542 (2003)CrossRefGoogle Scholar
  11. 11.
    Secker, A., Taubman, D.: Motion-compensated highly scalable video compression using an adaptive 3d wavelet transform based on lifting. In: IEEE Int. conf. Image Proc., pp. 1029–1032 (2001)Google Scholar
  12. 12.
    Secker, A., Taubman, D.: Highly scalable video compression using a lifting-based 3d wavelet transform with deformable mesh motion compensation. In: IEEE Int. conf. Image Proc., pp. 749–752 (2002)Google Scholar
  13. 13.
    Woods, et al.: Bi-Directional MC-EZBC with lifting implementation. IEEE Transaction of Circuits, Systems and Video Technology 14(10) (October 2004)Google Scholar
  14. 14.
    Choi, S., Woods, J.W.: Motion-compensated 3-D subband coding of video. IEEE Trans. Image Processing 8, 155–167 (1999)CrossRefGoogle Scholar
  15. 15.
    Antonini, M., Barlaud, M., Mathieu, P., Daubechies, I.: Image coding using wavelet transform. IEEE Trans. Image Processing 1, 205–220 (1992)CrossRefGoogle Scholar
  16. 16.
    Woods, et al.: Embedded image coding using zeroblocks of subband/wavelet coefficients and context modeling. Presented at the MPEG-4 Workshop and Exhibition at ISCAS 2000, Geneva, Switzerland (May 2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • A. K. Karunakar
    • 1
  • M. M. Manohara Pai
    • 1
  1. 1.Department of Information and Communication Technology, Manipal Institute of Technology, Manipal 576 104India

Personalised recommendations