Multimedia Tools and Applications

, Volume 43, Issue 1, pp 25–43 | Cite as

An adaptive GOP structure selection for haar-like MCTF encoding based on mutual information

  • Zhao-Guang Liu
  • Yu-Hua Peng
  • Yang Yang


In conventional motion compensated temporal filtering based wavelet coding scheme, where the group of picture structure and low-pass frame position are fixed, variations in motion activities of video sequences are not considered. In this paper, we propose an adaptive group of picture structure selection scheme, which the group of picture size and low-pass frame position are selected based on mutual information. Furthermore, the temporal decomposition process is determined adaptively according to the selected group of picture structure. A large amount of experimental work is carried out to compare the compression performance of proposed method with the conventional motion compensated temporal filtering encoding scheme and adaptive group of picture structure in standard scalable video coding model. The proposed low-pass frame selection can improve the compression quality by about 0.3–0.5 dB comparing to the conventional scheme in video sequences with high motion activities. In the scenes with un-even variation of motion activities, e.g. frequent shot cuts, the proposed adaptive group of picture size can achieve a better compression capability than conventional scheme. When comparing to adaptive group of picture in standard scalable video coding model, the proposed group of picture structure scheme can lead to about 0.2~0.8 dB improvements in sequences with high motion activities or shot cut.


Key frame Mutual information Motion compensated temporal filtering Group of picture 


  1. 1.
    Andreopoulos Y, Munteanu A, Barbarien J, Van der Schaar M, Cornelis J, Schelkens P (2004) In-band motion compensated temporal filtering. Signal Process Image Commun 19:653–673. doi: 10.1016/j.image.2004.05.007 CrossRefGoogle Scholar
  2. 2.
    Butz T, Thiran JP (2001) Shot boundary detection with mutual information. IEEE Int Conf Image Process 3:421–424Google Scholar
  3. 3.
    Cerneková Z, Pitas I, Nikou C (2006) Information theory-based shot cut/fade detection and video summarization. IEEE Trans Circuits Syst Video Technol 16:82–91. doi: 10.1109/TCSVT.2005.856896 CrossRefGoogle Scholar
  4. 4.
    Chen P Software package of MC-EZBC wavelet coder is publicly available at
  5. 5.
    Chen P (2003) Fully scalable subband/wavelet coding. Doctoral Thesis, Rensselaer Polytechnic Institute Troy, New YorkGoogle Scholar
  6. 6.
    Chen P, Woods JW (2004) Bidirectional MC-EZBC With Lifting Implementation. IEEE Trans Circuits Syst Video Technol 14:982–993Google Scholar
  7. 7.
    Chen C-Y, Huang C-T, Chen Y-H, Chien S-Y, Chen L-G (2006) System analysis of VLSI architecture for 5/3 and 1/3 motion-compensated temporal filtering. IEEE Trans Image Process 54:4004–4014Google Scholar
  8. 8.
    Cheng W, Liu Y, Xu D (2003) Shot boundary detection based on the knowledge of information theory. IEEE Int Conf Neural Netw Signal Process 2:1237–1241. doi: 10.1109/ICNNSP.2003.1281094 CrossRefGoogle Scholar
  9. 9.
    Choi S-J, Woods JW (1999) Motion-compensated 3-D subband coding of video. IEEE Trans Image Process 8:155–167. doi: 10.1109/83.743851 CrossRefGoogle Scholar
  10. 10.
    Dubios E, Sabri S (1984) Noise Reduction in Image Sequences Using Motion-Compensated Temporal Filtering. IEEE Trans Commun COM32(7):826–831CrossRefGoogle Scholar
  11. 11.
    Eeckhaut H, Harald D, Benjamin S, Mark C, & Dirk S (2005) A hardware-friendly wavelet entropy codec for scalable video, IEEE Design, Automation and Test in Europe Conference and Exhibition (DATE’05), vol. 3, pp. 14–19Google Scholar
  12. 12.
    Hsiang S-T, Woods JW (2001) Embedded video coding using invertible motion compensated 3-D subband/wavelet filter bank. Signal Process Image Commun. 16:705–724. doi: 10.1016/S0923-5965(01)00002-9 CrossRefGoogle Scholar
  13. 13.
    Lee J, Dickinson BW (1994) Temporally adaptive motion interpolation exploiting temporal masking in visual perception. IEEE Trans Image Process. 3:513–526. doi: 10.1109/83.334989 CrossRefGoogle Scholar
  14. 14.
    Lee J, Shin I, Park H (2006) Adaptive intra-frame assignment and bit-rate estimation for variable GOP length in H.264. IEEE Trans Circuits Syst Video Technol 16:1271–1279. doi: 10.1109/TCSVT.2006.881856 CrossRefGoogle Scholar
  15. 15.
    Leonardi R, Ohm J-R (2006) Wavelet Video Coding–an Overview. MPEG Workgroup Video Subgroup, ISO/IEC JTC1/SC29/WG11 W7824, Bangkok, ThailandGoogle Scholar
  16. 16.
    Li X (2004) Scalable video compression via overcomplete motion compensated wavelet coding. Signal Process Image Commun 19:637–651. doi: 10.1016/j.image.2004.05.006 CrossRefGoogle Scholar
  17. 17.
    Luo L, Li J, Li S, Zhuang Z, & Zhang Y-Q (2001) Motion compensated lifting wavelet and its application in video coding, IEEE Int. Conf. Multimedia and Expo ICME, pp. 365–368Google Scholar
  18. 18.
    Ohm J-R (1994) Three-dimensional subband coding with motion compensation. IEEE Trans Image Process 3:559–571. doi: 10.1109/83.334985 CrossRefGoogle Scholar
  19. 19.
    Ohm J-R (2005) Advances in Scalable Video Coding, Proceedings of the IEEE, vol. 93, Issue 1, pp. 42–56Google Scholar
  20. 20.
    Park GH, Park MW, Jeong S, Kim K, Hong J (2005) Improve SVC coding efficiency by adaptive GOP structure (SVC CE2). Joint Video Team (JVT) of ISO/IEC MPEG & ITU-T VCEG (ISO/IEC JTC1/SC29/WG11 and ITU-T SG16 Q.6) JVT-O018, KoreaGoogle Scholar
  21. 21.
    Park MW, Park GH, Jeong S, Suh D-Y, & Kim K (2007) Adaptive GOP Structure for Joint Scalable Video Coding, IEICE Trans. Communication, vol. E 90-B(2).Google Scholar
  22. 22.
    Park GH, Park MW, Jeong S, Cha J, Kim K, Hong J (2005) Adaptive GOP structure for SVC. ISO/IEC/JTC1/SC29/WG11/MPEG/ M11563, Hong KongGoogle Scholar
  23. 23.
    Pesquet-Popescu B, & Bottreau V (2001) Three-dimensional lifting schemes for motion-compensated video compression, IEEE Int. Conf. Acoustics, Speech, and Signal Processing, pp. 1793–1796Google Scholar
  24. 24.
    Secker A, Taubman D (2001) Motion-compensated highly-scalable video compression using an adaptive 3D wavelet transform based on lifting. IEEE Int. Conf. Image Process. 2:1029–1032Google Scholar
  25. 25.
    Song H, Kim J, Jay Kuo C-C (1999) Real-time encoding frame rate control for H.263+ video over the internet. Signal Process Image Commun. 15:127–148. doi: 10.1016/S0923-5965(99)00027-2 CrossRefGoogle Scholar
  26. 26.
    Tillier C, Pesquet-Popescu B, van der Schaar M (2006) 3-Band motion-compensated temporal structures for scalable video coding. IEEE Trans Image Process. 15:2545–2557. doi: 10.1109/TIP.2006.877411 CrossRefGoogle Scholar
  27. 27.
    Turaga DS, van der Schaar M, Andreopoulos Y, Munteanu A, Schelkens P (2005) Unconstrained motion compensated temporal filtering (UMCTF) for efficient and flexible interframe wavelet video coding. Signal Process Image Commun. 20:1–19. doi: 10.1016/j.image.2004.08.006 CrossRefGoogle Scholar
  28. 28.
    Wang L (2000) Rate control for MPEG video coding. Signal Process Image Commun. 15:493–511. doi: 10.1016/S0923-5965(99)00009-0 CrossRefGoogle Scholar
  29. 29.
    Wang Y, Cui S, Fowler JE (2006) 3-D Video coding with redundant-wavelet multihypothesis. IEEE Trans Circuits Syst Video Technol 16:166–177. doi: 10.1109/TCSVT.2005.861940 CrossRefGoogle Scholar
  30. 30.
    Wang Y-L, Wang J-X, Lai Y-W, & Su AWY (2005) Dynamic GOP structure determination for real-time MEPG-4 advanced simple profile video encoder. IEEE Int Conf Multimedia and Expo pp. 293–296Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  1. 1.School of Computer Science and TechnologyShandong Economic UniversityJinanChina
  2. 2.School of Information Science and EngineeringShandong UniversityJinanChina

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