Fast CU partitioning algorithm for HEVC intra coding using data mining

Abstract

The international standard of High Efficiency Video Coding (HEVC) improves the compression ratio by over 50 % compared to H.264/AVC, for the same perceptual quality. HEVC adopts flexible coding unit (CU) partitioning by applying recursive CU splitting into four sub-CUs, up to four depth levels, which causes a significant complexity increase. Intra-prediction coding in HEVC achieves high coding performance through the exhaustive evaluation of all available CU sizes, with up to 35 prediction modes for each CU, selecting the one with the lower rate distortion cost. This work presents a novel CU size classifier comprising an offline-trained decision tree with three hierarchical nodes. The decision rules computed in each node are based on the content texture properties of CUs as well as the inter-sub-CUs statistics of the same depth level. Our approach can reduce the number of CU sizes to be checked by the Rough Mode Decision and Rate Distortion Optimization stages of intra-prediction coding. The experimental results show that the proposed algorithm can achieve over 50 % coding time reduction, with no quality penalty in terms of the Peak Signal to Noise Ratio, and just a low bit rate increase (2 %) compared to the HEVC reference model. A performance comparison with state-of-the-art proposals shows that this algorithm surpasses the best proposal in terms of time reduction, for the same coding performance penalty.

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References

  1. 1.

    Advanced video coding for generic audiovisual services,Rec.ITU-T H.264 and ISO/IEC 14496–10 (MPEG-4 AVC), 2012

  2. 2.

    Bjøntegaard G (2001) Calculation of average PSNR differences between RD-curves, ITU-T SG16 Q.6 document, VCEG-M33, Austin, US

  3. 3.

    Bossen F (2013) Common test conditions and software reference configurations, document JCTVC-L1100, ITU-T/ISO/IEC joint collaborative team on video coding (JCT-VC), 12th meeting: Geneve, CH

  4. 4.

    Carrillo P, Pin T, Kalva H (2010) Low complexity H.264 video encoder design using machine learning techniques. Consum Electron (ICCE) 2010 Dig Tech Pa Int Conf 461–462

  5. 5.

    Chen L-S, Lin J-Y (2013) A study on review manipulation classification using decision tree. Serv Syst Serv Manag (ICSSSM) 2013 10th Int Conf 680–685

  6. 6.

    Chen G, Pei Z, Sun L, Liu Z, Ikenaga T (2013) Fast intra prediction for HEVC based on pixel gradient statistics and mode refinement. Sig Inf Process (ChinaSIP) 2013 I.E. China Summit Int Conf 514–517

  7. 7.

    Correa G, Assuncao P, Agostini L, da Silva Cruz LA (2012) Performance and computational complexity assessment of high-efficiency video encoders. Circ Syst Video Technol IEEE Trans 22(12):1899–1909

    Article  Google Scholar 

  8. 8.

    da Silva TL, Agostini LV, da Silva Cruz LA (2012) Fast HEVC intra prediction mode decision based on EDGE direction information. Sig Process Conf (EUSIPCO) 2012 Proc 20th Eur 1214–1218

  9. 9.

    Dufaux F, Sullivan GJ, Ebrahimi T (2009) The JPEG XR image coding standard [Standards in a Nutshell]. IEEE Sig Process Mag 26(6):195–199

  10. 10.

    Fernández-Escribano G, Jillani R, Holder C, Kalva H, Martinez JL, Cuenca P (2008) Video encoding and transcoding using machine learning, multimedia data mining: held in conjunction with the ACM SIGKDD 2008 (MDM ’08), 9th International Workshop on, pp. 53–62, Las Vegas, Nevada

  11. 11.

    Fernández-Escribano G, Kalva H, Cuenca P, Orozco-Barbosa L, Garrido A (2008) A fast MB mode decision algorithm for MPEG-2 to H.264 P-frame transcoding. Circ Syst Video Technol IEEE Trans 18(2):172–185

    Article  Google Scholar 

  12. 12.

    Fernandez-Escribano G, Kalva H, Martinez JL, Cuenca P, Orozco-Barbosa L, Garrido A (2010) An MPEG-2 to H.264 video transcoder in the baseline profile. Circ Syst Video Technol IEEE Trans 20(5):763–768

    Article  Google Scholar 

  13. 13.

    H.264/AVC reference software [Online]. Available: http://iphome.hhi.de/suehring/tml/

  14. 14.

    Hall M, Frank E, Holmes G, Pfahringer B, Reutemann P, Witten IH (2009) The WEKA data mining software: an update; SIGKDD explorations 11(1)

  15. 15.

    Han W-J, Min J, Kim I-K, Alshina E, Alshin A, Lee T, Chen J, Seregin V, Lee S, Hong YM, Cheon M-S, Shlyakhov N, McCann K, Davies T, Park J-H (2010) Improved video compression efficiency through flexible unit representation and corresponding extension of coding tools. IEEE Trans Circuits Syst Video Technol 20(12):1709–1720

  16. 16.

    Hanhart P, Rerabek M, De Simone F, Ebrahimi T (2012) Subjective quality evaluation of the upcoming HEVC video compression standard. Proc. SPIE 8499, Applications of digital image processing XXXV, 84990V

  17. 17.

    High efficiency video coding, Rec. ITU-T H.265 and ISO/IEC 23008–2, Jan. 2013

  18. 18.

    Huang H, Zhao Y, Lin C, Bai H (2013) Fast bottom-up pruning for HEVC intraframe coding. In: Visual Communications and Image Processing (VCIP), 17–20 Nov 2013, pp 1–5

  19. 19.

    Hulse JV, Khoshgoftaar TM, Napolitano A (2007) Experimental perspectives on learning from imbalanced data. Proc 24th Int Conf Mach Learn 935–942

  20. 20.

    ISO/IEC 23008–2:2013. Information technology -- High efficiency coding and media delivery in heterogeneous environments -- Part 2: high efficiency video coding

  21. 21.

    ITU-T Rec. T.800 and ISO/IEC 15444–1. JPEG2000 image coding system: core coding system (JPEG2000 Part 1), 2000

  22. 22.

    Japkowicz N (ed) Proceedings of the AAAI’2000. Workshopon learning from imbalanced data sets,. AAAI tech report WS-00-05

  23. 23.

    JCT-VC test sequences. [Online]. Available:ftp://hevc@ftp.tnt.uni-hannover.de/testsequences/

  24. 24.

    Jiang W, Ma H, Chen Y (2012) Gradient based fast mode decision algorithm for intra prediction in HEVC. Consum Electron Commun Netw (CECNet) 2012 2nd Int Conf 1836–1840

  25. 25.

    Jillani R, Kalva H (2009) Low complexity intra MB encoding in AVC/H.264. IEEE Trans Consum Electron 55(1):277–285

  26. 26.

    Joint collaborative team on video coding reference software, ver. HM 16.6 [Online]. Available: https://hevc.hhi.fraunhofer.de/

  27. 27.

    Kim Y, Jun D, Jung S-H, Choi JS, Kim J (2013) A fast intra-prediction method in HEVC using rate-distortion estimation based on Hadamard transform. ETRI J 35(2):270–280

    Article  Google Scholar 

  28. 28.

    Korhonen J, You J (2010) Improving objective video quality assessment with content analysis. In: Proceedings of VPQM '10, Scottsdale, Jan 2010

  29. 29.

    Lainema J, Bossen F, Han W-J, Min J, Ugur K (2012) Intra coding of the HEVC standard. IEEE Trans Circ Syst Video Technol 22(12):1792–1801

  30. 30.

    Martínez JM (2004) MPEG-7 overview (version 10), MPEG document, ISO/IEC JTC1/SC29/WG11 N6828, Palma de Mallorca

  31. 31.

    Martinez JL, Fernandez-Escribano G, Kalva H, Weerakkody WARJ, Fernando WAC, Garrido A (2008) Feedback free DVC architecture using machine learning. Image Process 2008 ICIP 2008 15th IEEE Int Conf 1140–1143

  32. 32.

    Min J, Lee S, Kim I, Han W-J, Lainema J, Ugur K (2010) Unification of the directional intra prediction methods in TMuC, JCTVC-B100. Geneva

  33. 33.

    Nguyen T, Marpe D (2012) Performance analysis of HEVC-based intra coding for still image compression. Picture Coding Symp (PCS) 2012 233–236

  34. 34.

    Ohm J, Sullivan GJ, Schwarz H, Tan TK, Wiegand T (2012) Comparison of the coding efficiency of video coding standards—including high efficiency video coding (HEVC). Circ Syst Video Technol IEEE Trans 22(12):1669–1684

    Article  Google Scholar 

  35. 35.

    Pan F, Lin X, Rahardja S, Lim KP, Li ZG, Wu D, Wu S (2005) Fast mode decision algorithm for intra prediction in H.264/AVC video coding. IEEE Trans Circ Syst Video Technol 15(7):813–822

  36. 36.

    Panusopone K, Fang X, Wang L (2011) Efficient transform unit representation, Doc. JCTVC-D250

  37. 37.

    Piao Y, Min JH, Chen J (2010) Encoder improvement of unified intra prediction, JCTVC-C207, JCT-VC of ISO/IEC and ITU-T. Guangzhou

  38. 38.

    Pinson MH, Wolf S (2004) A new standardized method for objectively measuring video quality. IEEE Trans Broadcast 50(3):312–322

    Article  Google Scholar 

  39. 39.

    Quinlan J-R (1993) C4.5: programs for machine learning. Morgan- Kaufmann, San Francisco

    Google Scholar 

  40. 40.

    Recommendation ITU-T P.910. Subjective video quality assessment methods for multimedia applications. International Telecommunication Union, Geneva (1999)

  41. 41.

    Saxena A, Fernandes FC (2013) DCT/DST-based transform coding for intra prediction in image/video coding. IEEE Trans Image Process 22(10):3974–3981

  42. 42.

    Shen L, Zhang Z, An P (2013) Fast CU size decision and mode decision algorithm for HEVC intra coding. Consum Electron IEEE Trans 59(1):207–213

    Article  Google Scholar 

  43. 43.

    Sullivan G, Minoo K (2012) Objective quality metric and alternative methods for measuring coding efficiency, document JCTVC-H0012, ITU-T/ISO/IEC joint collaborative team on video coding (JCT-VC), 8th meeting: San Jose, CA, USA

  44. 44.

    Sullivan GJ, Ohm J, Han W-J, Wiegand T, Wiegand T (2012) Overview of the high efficiency video coding (HEVC) standard. IEEE Trans Circuits Syst Video Technol 22(12):1649–1668

  45. 45.

    Tian G, Goto S (2012) Content adaptive prediction unit size decision algorithm for HEVC intra coding. Picture Coding Symp (PCS) 2012 405–408

  46. 46.

    Wang L-l, Siu W-C (2013) Novel adaptive algorithm for intra prediction with compromised modes skipping and signaling processes in HEVC. Circ Syst Video Technol IEEE Trans 23(10):1686–1694

    Article  Google Scholar 

  47. 47.

    Xiang L, Wien M, Ohm JR (2011) Rate-complexity-distortion optimization for hybrid video coding. Circ Syst Video Technol IEEE Trans 21(7):957–970

    Article  Google Scholar 

  48. 48.

    Yan S, Hong L, He W, Wang Q (2012) Group-based fast mode decision algorithm for intra prediction in HEVC. In: 2012 Eighth International Conference on Signal Image Technology and Internet Based Systems (SITIS), 25–29 Nov 2012, pp 225–229

  49. 49.

    Yao Y, Li X, Lu Y (2014) Fast intra mode decision algorithm for HEVC based on dominant edge assent distribution. Multimedia Tools Appl J. Springer US. 1–19

  50. 50.

    Yu H, Winkler S (2013) Image complexity and spatial information. In: 2013 Fifth International Workshop on Quality of Multimedia Experience (QoMEX), 3–5 July 2013, pp 12–17

  51. 51.

    Zhao L, Zhang L, Ma S, Zhao D (2011) Fast mode decision algorithm for intra prediction in HEVC. In: Visual Communications and Image Processing (VCIP), 2011 IEEE, 6-9 Nov 2011, pp 1–4

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Acknowledgments

This work has been jointly supported by the MINECO and European Commission (FEDER funds) under the project TIN2012-38341-C04-04.

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Correspondence to Damián Ruiz.

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Ruiz, D., Fernández-Escribano, G., Adzic, V. et al. Fast CU partitioning algorithm for HEVC intra coding using data mining. Multimed Tools Appl 76, 861–894 (2017). https://doi.org/10.1007/s11042-015-3014-6

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Keywords

  • HEVC
  • Rate distortion optimization
  • Intra-prediction
  • Machine learning
  • Coding tree block