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An improved 3D wavelet-based scalable video coding codec for MC-EZBC

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Abstract

With the rapid growth of modern multimedia applications, 3D wavelet-based scalable video coding (SVC) codec has received considerable attention lately because of its high coding performance and flexibility in bitstream scalability. It combines the motion-compensated temporal filtering (MCTF) together with the spatial decomposition to produce an embedded bitstream offering various levels of video quality over the heterogeneous networks. However, in the existing 3D wavelet-based SVC schemes, where the block types for block matching algorithms are limited, weighting matrices for block-wise motion compensation are fixed, and variations in activities of temporal subbands are not considered in the selection of the Lagrange multiplier for mode decision. In this paper, our major contribution is to provide some recent extensions to the well-known scalable subband/wavelet video codec Motion-Compensated Embedded Zero Block Coding (MC-EZBC) using three novel and content adaptive algorithms. Firstly, the enhanced hierarchical variable size block matching (Enhanced HVSBM) algorithm is proposed for the variable block size motion estimation. Then, the rate-distortion optimization (RDO) based adaptive Lagrange multiplier selection model for mode decision is presented. Finally, we introduce the adaptive weighting matrices design for overlapped block motion compensation (OBMC). Experimental results show that all the three proposed algorithms significantly improve the overall coding performance of MC-EZBC. Comparisons with other popular wavelet-based SVC codecs demonstrate the effectiveness of our improved codec in terms of both video quality assessment and computational complexity.

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References

  1. Adami N, Signoroni A, Leonardi R (2007) State-of-the-art and trends in scalable video compression with wavelet-based approaches. IEEE Trans Circuits Syst Video Technol 17(9):1238–1255

    Article  Google Scholar 

  2. Amel A M, Abdessalem B A, Abdellatif M (2010) Video shot boundary detection using motion activity descriptor. J Telecommun 2(1):54–59

    Google Scholar 

  3. Andreopoulos Y, Munteanu A, Van Der Auvera G, Cornelis J P H, Schelkens P (2005) Complete-to-overcomplete discrete wavelet transforms: theory and applications. IEEE Trans Signal Process 53(4):1398–1412

    Article  MathSciNet  Google Scholar 

  4. Antonini M, Barlaud M, Mathieu P, Daubechies I (1992) Image coding using wavelet transform. IEEE Trans Image Process 1(2):205–220

    Article  Google Scholar 

  5. Cai X, Zhang Y, Zhang J, Van H (2012) Enhanced hierarchal variable size block matching method in MC-EZBC. IEEE Int Conf Signal Process 2:1047–1050

    Google Scholar 

  6. Chen J, Zhang W, Wang Y (2005) Enhanced motion coding in MC-EZBC. In: Proceedings of the SPIE visual communications and image processing, vol 5960, pp 1–9

  7. Chen P, Hanke K, Rusert T, Woods J W (2003) Improvements to the MC-EZBC scalable video coder. IEEE Int Conf Image Process 2:II-81-4

    Google Scholar 

  8. Chen P, Woods J W (2004) Bidirectional MC-EZBC with lifting implementation. IEEE Trans Circuits Syst Video Technol 14(10):1183–1194

    Article  Google Scholar 

  9. Choi S J, Woods J W (1999) Motion-compensated 3-D subband coding of video. IEEE Trans Image Process 8(2):155–167

    Article  Google Scholar 

  10. Dalal N, Triggs B (2005) Histograms of oriented gradients for human detection. IEEE Int Conf Comput Vis Pattern Recognit 881:886–893

    Google Scholar 

  11. Devore J, Farnum N, Doi J (2013) Applied statistics for engineers and scientists. Cengage Learning Press

  12. Dirfaux F (2000) Key frame selection to represent a video. IEEE Int Conf Image Process 272:275–278

    Google Scholar 

  13. Fradj B B, Zaid A O (2014) Scalable video coding using motion-compensated temporal filtering and intra-band wavelet based compression. Multimed Tools Appl 69 (3):1089–1109

    Article  Google Scholar 

  14. Golwelkar A, Woods J W (2007) Motion-compensated temporal filtering and motion vector coding using biorthogonal filters. IEEE Trans Circuits Syst Video Technol 17(4):417–428

    Article  Google Scholar 

  15. Gonzalez-de-Suso J L, Jimenez-Moreno A, Martinez-Enriquez E, Diaz-de-Maria F (2014) Improved method to select the Lagrange multiplier for rate-distortion based motion estimation in video coding. IEEE Trans Circuits Syst Video Technol 24 (3):452–464

    Article  Google Scholar 

  16. Hanke K, Rusert T, Ohm J R (2003) Motion-compensated 3D video coding using smooth transitions. In: Proceedings of the SPIE visual communications and image processing, pp 933–940

  17. Hsiang S T, Woods J W (2000) Embedded image coding using zeroblocks of subband/wavelet coefficients and context modeling. IEEE Int Conf Circuits Syst 3:662–665

    Google Scholar 

  18. Hsiang S T, Woods J W (2001) Embedded video coding using invertible motion compensated 3-D subband/wavelet filter bank. Signal Process Image Commun 16(8):705–724

    Article  Google Scholar 

  19. Hsiang S T, Woods J W, Ohm J R (2004) Invertible temporal subband/wavelet filter banks with half-pixel-accurate motion compensation. IEEE Trans Image Process 13(8):1018–1028

    Article  Google Scholar 

  20. Huang T U (2014) Improved MC-EZBC structure for bitstream extraction and live streaming. Int Conf Comput Intell Des 1:365–368

    Google Scholar 

  21. Jeannin S, Divakaran A (2001) MPEG-7 visual motion descriptors. IEEE Trans Circuits Syst Video Technol 11(6):720–724

    Article  Google Scholar 

  22. Jonathan K, Russell M (2000) Motion estimation methods for overlapped block motion compensation. IEEE Trans Image Process 9(9):1509–1521

    Article  Google Scholar 

  23. Kao M P (2008) A block-based scalable motion model for highly scalable video coding. Doctoral Thesis, University of California, San Diego

  24. Karlsson G, Vetterli M (1988) Three dimensional sub-band coding of video. IEEE Int Conf Acoust Speech Signal Process 1102:1100–1103

    Google Scholar 

  25. Li X, Amon P, Hutter A, Kaup A (2009) Lagrange multiplier selection for rate-distortion optimization in SVC. In: IEEE international conference on picture coding symposium, pp 1–4

  26. Li X, Oertel N, Hutter A, Kaup A (2007) Advanced Lagrange multiplier selection for hybrid video coding. IEEE International conference on multimedia and Expo, pp 364–367

  27. Marzougui M, Zoghlami A, Atri M, Tourki R (2013) Preliminary study of block matching algorithms for wavelet-based t + 2D video coding. In: International conference on systems, signals & devices, pp 1–6

  28. Ohm J R (1994) Three-dimensional subband coding with motion compensation. IEEE Trans Image Process 3(5):559–571

    Article  Google Scholar 

  29. Omidyeganeh M, Ghaemmaghami S, Shirmohammadi S (2013) Application of 3D-wavelet statistics to video analysis. Multimed Tools Appl 65(3):441–465

    Article  Google Scholar 

  30. Orchard M T, Sullivan G J (1994) Overlapped block motion compensation: an estimation-theoretic approach. IEEE Trans Image Process 3(5):693-:699

  31. Peker K A, Divakaran A (2004) Framework for measurement of the intensity of motion activity of video segments. J Vis Commun Image Represent 15(3):265–284

    Article  Google Scholar 

  32. Peker K A, Divakaran A, Papathomas T V (2001) Automatic measurement of intensity of motion activity of video segments. In: Proceedings in storage and retrieval for media database, pp 341–351

  33. Smeaton A F, Over P, Doherty A R (2010) Video shot boundary detection: Seven years of TRECVid activity. Comput Vis Image Underst 114(4):411–418

    Article  Google Scholar 

  34. Spiteri T, Nunez-Yonez J (2012) Scalable video coding with multi-layer motion vector palettes. IET Image Process 6(9):1319–1330

    Article  MathSciNet  Google Scholar 

  35. Taubman D, Zakhor A (1994) Multirate 3-D subband coding of video. IEEE Trans Image Process 3:572–588

    Article  Google Scholar 

  36. Tsai S S, Hang H M (2004) Motion information scalability for MC-EZBC. Signal Process Image Commun 19(7):675–684

    Article  Google Scholar 

  37. Wan S, Yang F, Izquierdo E (2009) Lagrange multiplier selection in wavelet-based scalable video coding for quality scalability. Signal Process Image Commun 24(9):730–739

    Article  Google Scholar 

  38. Wang H, Klaser A, Schmid C, Liu C (2011) Action recognition by dense trajectories. In: IEEE International Conference in computer vision and pattern recognition, pp 3169–3176

  39. Wang M, Van der Schaar M (2006) Operational rate-distortion modeling for wavelet video coders. IEEE Trans Signal Process 54(9):3505–3516

    Article  Google Scholar 

  40. Wang Z, Bovik A C, Sheikh H R, Simoncelli E P (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13 (4):600–612

    Article  Google Scholar 

  41. Wien M, Rusert T, Hanke K (2004) RWTH proposal for scalable video coding technology. Technical Report ISO/IEC/JTC1/SC29/WG11/MPEG2004/M10569/S16

  42. Woods J W, Wu Y, Cohen R A (2010) Overlapped block motion compression for variable size blocks in the context of MCTF scalable video coders. U. S. Patent No.7,653,133 B2

  43. Wu Y (2005) Fully scalable subband/wavelet video coding system. Doctoral Thesis, Rensselaer Polytechnic Institute Troy, New York

  44. Wu Y, Hanke K, Rusert T, Woods J W (2008) Enhanced MC-EZBC scalable video coder. IEEE Trans Circuits Syst Video Technol 18(10):1432–1436

    Article  Google Scholar 

  45. Wu Y, Woods J W (2004) Directional spatial I-blocks for the MC-EZBC video coder. IEEE Int Conf Acoust Speech Signal Process 3:129–132

    Google Scholar 

  46. Yan C, Zhang Y, Xu J, Dai F, Zhang J, Dai Q, Wu F (2014) Efficient parallel framework for HEVC motion estimation on many-core processors. IEEE Trans Circuits Syst Video Technol 24(12):2077–2089

    Article  Google Scholar 

Download references

Acknowledgments

This work is supported by the National Natural Science Foundation of China (NSFC) Projects No.61173110 and No.61301237. The authors would like to thank the editors and anonymous reviewers for their constructive and insightful comments to this paper. They would also like to thank the experts for their valuable contributions toward the successful completion of these important video coding standards and fruitful discussions. In particular, the authors also appreciate the research group at RWTH Aachen University and the CIPR lab at RPI for providing the source codes of their latest MC-EZBC coding scheme for academic and research usage.

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Correspondence to Guizhong Liu.

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Chen, Y., Liu, G. & Yao, J. An improved 3D wavelet-based scalable video coding codec for MC-EZBC. Multimed Tools Appl 76, 7595–7632 (2017). https://doi.org/10.1007/s11042-016-3387-1

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  • DOI: https://doi.org/10.1007/s11042-016-3387-1

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