Advertisement

Multimedia Tools and Applications

, Volume 56, Issue 3, pp 385–417 | Cite as

Efficient adaptive-shape partitioning of video

  • Kenneth VermeirschEmail author
  • Jan De Cock
  • Stijn Notebaert
  • Peter Lambert
  • Joeri Barbarien
  • Adrian Munteanu
  • Rik Van de Walle
Article

Abstract

While many recent international video coding standards, especially H.264/MPEG-4 AVC, leverage block size adaptivity in motion estimation, the rate-distortion boundary can be pushed further by allowing even more freedom in the partitioning process of inter pictures. Adaptive-shape partitioning, which allows blocks to be partitioned along a straight line that runs through the block at a freely chosen angle and position, complements the regular subblock partitioning, allowing the encoder to better adapt to the local characteristics of the motion activity in a video sequence. However, the technique demands excessive encoder resources to exhaust the large search space. This paper is the result of an investigation into the relative rate-distortion importance of the various adaptive-shape modes, both in terms of the angle of the partition boundary and of its location within a block. We find that a significant reduction of the search space with a factor of up to 40 can be accomplished, while retaining 50 to 90% of the compression gain obtained in the state of the art. This allows encoders to operate at much lower complexity levels and also reduces the signaling overhead associated with adaptive-shape partitioning. Based on our observations, we formulate a number of approaches to trade off compression performance against encoder complexity. Furthermore we discuss the use of various schemes of overlapping motion estimation along the partition boundary, an aspect which is currently left unaddressed in the literature on adaptive-shape partitioning. We introduce the use of shape-adaptive transforms for the motion compensated signal, to avoid the condition that arises with adaptive-shape partitioning where a partition boundary lies inside a transform block. The result is a reduction in ringing artifacts while maintaining objective quality.

Keywords

Video coding Partitioning Motion compensation Complexity Shape-adaptive transformation 

Notes

Acknowledgements

The research activities described in this paper were funded by Ghent University, the Interdisciplinary Institute for Broadband Technology (IBBT), the Institute for the Promotion of Innovation by Science and Technology in Flanders (IWT), the Fund for Scientific Research–Flanders (FWO–Flanders), and the European Union.

References

  1. 1.
    Bjøntegaard G (2001) VCEG-M33: calculation of average PSNR differences between RD-curves. ITU-T Q.6/16 VCEG. http://wftp3.itu.int/av-arch/video-site/0104_Aus/. Accessed 20 May 2010
  2. 2.
    Bresenham JE (1968) Algorithm for computer control of a digital plotter. IBM Syst J 4(1):25–30CrossRefGoogle Scholar
  3. 3.
    Cheong HY, Tourapis AM (2003) Fast motion estimation within the H.264 codec. In: Proc. of int. conf. multimedia & expo (ICME), IEEEGoogle Scholar
  4. 4.
    Divorra Escoda O, Yin P, Dai C, Li X (2007) Geometry-adaptive block partitioning for video coding. In: Int. conf. acoustic, speech, and signal proc (ICASSP) IEEEGoogle Scholar
  5. 5.
    Divorra O, Yin P, Gomila C (2007) VCEG-AG13: geometry-adaptive block partitioning on B-frames. ITU-T Q.6/16 VCEG. http://wftp3.itu.int/av-arch/video-site/0710_She/. Accessed 20 May 2010
  6. 6.
    Fukuhara T, Asai K, Murakami T (1997) Very low bit-rate video coding with block partitioning and adaptive selection of two time-differential frame memories. IEEE Trans Circuits Syst Video Technol 7(1):212–220CrossRefGoogle Scholar
  7. 7.
    Flierl M, Girod B (2001) Multihypothesis motion estimation for video coding. In: Proceedings of the data compression conference, pp 27–29Google Scholar
  8. 8.
    Flierl M, Wiegand T, Girod B (2002) Rate-constrained multihypothesis prediction for motion compensated video compression. IEEE Trans Circuits Syst Video Technol 12(11):957–968CrossRefGoogle Scholar
  9. 9.
    Girod B (2000) Efficiency analysis of multihypothesis motion-compensated prediction for video coding. IEEE Trans Image Process 9(2):173–183CrossRefGoogle Scholar
  10. 10.
    Golomb SW (1966) Run-length encodings. IEEE Trans Inf Theory 12:399–401MathSciNetzbMATHCrossRefGoogle Scholar
  11. 11.
    Hung EM, De Queiroz RL, Mukherjee, D (2006) On macroblock partition for motion compensation. In: Proc. IEEE int. conf. image process (ICIP)Google Scholar
  12. 12.
    ITU (2005) ITU-T recommendation H.264. Advanced video coding for generic audiovisual servicesGoogle Scholar
  13. 13.
    ITU (2005) ITU-T recommendation H.263. Video coding for low bit rate communicationGoogle Scholar
  14. 14.
    ITU-T Q.6/16 Video coding experts group (VCEG), Key technological advancements (KTA) software. http://iphome.hhi.de/suehring/tml/download/KTA/. Accessed 20 May 2010
  15. 15.
    Kato S, Sekiguchi S, Adachi S, Etoh M (2002) Performance evalutation on H.26L-based motion compensation with segmented multiple reference frames. In: Proc. IEEE int. conf. image process (ICIP)Google Scholar
  16. 16.
    Kato S, Sugimoto K, Moschetti F, Boon CS (2004) Hierarchical mode search with classification of bisectional prediction modes based on the position of motion boundary. In: Proc. IEEE int. conf. image process (ICIP)Google Scholar
  17. 17.
    Kondo S, Sasai H (2005) A motion compensation technique using sliced blocks in hybrid video coding. In: Proc. IEEE int. conf. image process (ICIP)Google Scholar
  18. 18.
    Kondo S, Sasai H (2005) A motion compensation technique using sliced blocks and its application to hybrid video coding. In: Visual communications and image processing 2005 SPIEGoogle Scholar
  19. 19.
    Kordasiewicz RC, Gallant MD, Shirani S (2007) Modeling quantization of affine motion vector coefficients. IEEE Trans Circuits Syst Video Technol 17(1):86–97CrossRefGoogle Scholar
  20. 20.
    Marpe D, Schwarz H, Wiegand T (2003) Context-based adaptive binary arithmetic coding in the H.264/AVC video compression standard. IEEE Trans. Circuits Syst Video Technol 13(7):620–636CrossRefGoogle Scholar
  21. 21.
    Orchard M, Sullivan G (1994) Overlapped block motion compensation: an estimation-theoretic approach. IEEE Trans Image Process 3(5):693–699CrossRefGoogle Scholar
  22. 22.
    Puri A, Eleftheriadis A (1998) MPEG-4: an object-based multimedia coding standard supporting mobile applications. Mob Netw Appl 3(1):5–32CrossRefGoogle Scholar
  23. 23.
    Rajagopalan R, Feig E, Orchard M (1998) Motion optimization of ordered blocks for overlapped block motion compensation. IEEE Trans Circuits Syst Video Technol 8(2):119–123CrossRefGoogle Scholar
  24. 24.
    Ribas-Corbera J, Neuhoff DL (1998) Optimizing block size in motion-compensated video coding. J Electron Imaging 7(1):155–165CrossRefGoogle Scholar
  25. 25.
    Shen J, Chan WY (1999) Vector quantization of affine motion models. In: Proc. IEEE int. conf. image process (ICIP)Google Scholar
  26. 26.
    Sikora T, Makai B (1995) Shape-adaptive DCT for generic coding of video. IEEE Trans Circuits Syst Video Technol 5(1):59–62CrossRefGoogle Scholar
  27. 27.
    Sikora T (1995) Low complexity shape-adaptive DCT for coding of arbitrarily shaped image segments. Signal Process Image Commun 7:381–395CrossRefGoogle Scholar
  28. 28.
    Sullivan G (1993) Multi-hypothesis motion compensation for low bit-rate video coding. In: Proceedings of the IEEE international conference on acoustics, speech, and signal processing, vol 5, pp 437–440Google Scholar
  29. 29.
    Sullivan GJ, Wiegand T (1998) Rate-distortion optimization for video compression. IEEE Signal Process Mag 15:74–90CrossRefGoogle Scholar
  30. 30.
    Tan TK, Sullivan G, Wedi T (2008) VCEG-AH10r1: recommended simulation common conditions for coding efficiency experiments, revision 2. ITU-T Q.6/16 VCEG. http://wftp3.itu.int/av-arch/video-site/0701_Mar/. Accessed 20 May 2010
  31. 31.
    Tao B, Orchard M (2001) A parametric solution for optimal overlapped block motion compensation. IEEE Trans Image Process 10(3):341–350zbMATHCrossRefGoogle Scholar
  32. 32.
    Tourapis AM (2002) Enhanced predictive zonal search for single and multiple frame motion estimation. In: Proc. of visual comm. and image proc. (VCIP), pp 1069–1079Google Scholar
  33. 33.
    Vermeirsch K, De Cock J, Notebaert S, Lambert P, Van de Walle R (2008) Increased flexibility in inter picture partitioning. In: Proc. of int. symp. on multimedia sig. proc (MMSP)Google Scholar
  34. 34.
    Wedi T (2006) Adaptive interpolation filters and high-resolution displacements for video coding. IEEE Trans Circuits Syst Video Technol 16(4):484–491CrossRefGoogle Scholar
  35. 35.
    Wiegand T, Steinback E, Girod B (2005) Affine multipicture motion-compensated prediction. IEEE Trans Circuits Syst Video Technol 15(2):197–209CrossRefGoogle Scholar
  36. 36.
    Wiegand T, Sullivan GJ, Bjøntegaard G, Luthra A (2003) Overview of the H.264/AVC video coding standard. IEEE Trans Circuits Syst Video Technol 13(7):560–576CrossRefGoogle Scholar
  37. 37.
    Wiegand T, Zhang X, Girod B (1999) Long-term memory motion-compensated prediction. IEEE Trans Circuits Syst Video Technol 9(1):70–84CrossRefGoogle Scholar
  38. 38.
    Zhang K, Bober M, Kittler J (1995) Variable block size video coding with motion prediction and motion segmentation. In: Proc. SPIE digital video compression: algorithms and technologiesGoogle Scholar
  39. 39.
    Zhang K, Bober M, Kittler J (1996) A hybrid codec for very low bit rate video coding. In: Proc. IEEE int. conf. image process (ICIP)Google Scholar
  40. 40.
    Zhang K, Bober M, Kittler J (1997) Image sequence coding using multiple-level segmentation and affine motion estimation. IEEE J Sel Areas Commun 15(9):1704–1713CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Kenneth Vermeirsch
    • 1
    Email author
  • Jan De Cock
    • 1
  • Stijn Notebaert
    • 1
  • Peter Lambert
    • 1
  • Joeri Barbarien
    • 2
  • Adrian Munteanu
    • 2
  • Rik Van de Walle
    • 1
  1. 1.Multimedia Lab of the Department of Electronics and Information SystemsGhent UniversityGhentBelgium
  2. 2.Department of Electronics and Information Processing (ETRO)Vrije Universiteit BrusselBrusselsBelgium

Personalised recommendations