skip to main content
research-article

Adaptive Fractional-Pixel Motion Estimation Skipped Algorithm for Efficient HEVC Motion Estimation

Authors Info & Claims
Published:04 January 2018Publication History
Skip Abstract Section

Abstract

High-Efficiency Video Coding (HEVC) efficiently addresses the storage and transmit problems of high-definition videos, especially for 4K videos. The variable-size Prediction Units (PUs)--based Motion Estimation (ME) contributes a significant compression rate to the HEVC encoder and also generates a huge computation load. Meanwhile, high-level encoding complexity prevents widespread adoption of the HEVC encoder in multimedia systems. In this article, an adaptive fractional-pixel ME skipped scheme is proposed for low-complexity HEVC ME. First, based on the property of the variable-size PUs--based ME process and the video content partition relationship among variable-size PUs, all inter-PU modes during a coding unit encoding process are classified into root-type PU mode and children-type PU modes. Then, according to the ME result of the root-type PU mode, the fractional-pixel ME of its children-type PU modes is adaptively skipped. Simulation results show that, compared to the original ME in HEVC reference software, the proposed algorithm reduces ME encoding time by an average of 63.22% while encoding efficiency performance is maintained.

References

  1. A. Abdelazim, W. Masri, and B. Noaman. 2014. Motion estimation optimization tools for the emerging high efficiency video coding (HEVC). Proceedings of SPIE 9029, 902905--902905--8. DOI:http://dx.doi.org/10.1117/12.2041166 Google ScholarGoogle ScholarCross RefCross Ref
  2. G. Bjontegaard. 2001. Calculation of average PSNR differences between RD curves. In Proceedings of the ITU-T VCEG 13th VCEG-M33 Meeting. Document VCEG--M33.Google ScholarGoogle Scholar
  3. S. G. Blasi, I. Zupancic, E. Izquierdo, and E. Peixoto. 2015. Adaptive precision motion estimation for HEVC coding. In Picture Coding Symposium (PCS’15). 144--148. DOI:http://dx.doi.org/10.1109/PCS.2015.7170064 Google ScholarGoogle ScholarCross RefCross Ref
  4. F. Bossen. 2012. Common test conditions and software reference configurations. In ITU-T/ISO/IEC Joint Collaborative Team on Video Coding (JCT-VC’12). Document JCTVC--J1100.Google ScholarGoogle Scholar
  5. W. Dai, O. C. Au, C. Pang, L. Sun, R. Zou, and S. Li. 2012. A novel fast two step sub-pixel motion estimation algorithm in HEVC. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP’12). 1197--1200. DOI:http://dx.doi.org/10.1109/ICASSP.2012.6288102 Google ScholarGoogle ScholarCross RefCross Ref
  6. T. Dutta and H. P. Gupta. 2017. An efficient framework for compressed domain watermarking in P frames of high-efficiency video coding (HEVC)-encoded video. ACM Transactions on Multimedia Computing, Communications, and Applications 13, 1, Article 12, 24 pages. DOI:http://dx.doi.org/10.1145/3002178 Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. L. Gao, S. Dong, W. Wang, R. Wang, and W. Gao. 2015. A novel integer-pixel motion estimation algorithm based on quadratic prediction. In IEEE International Conference on Image Processing (ICIP’15). 2810--2814. DOI:http://dx.doi.org/10.1109/ICIP.2015.7351315 Google ScholarGoogle ScholarCross RefCross Ref
  8. N. Hu and E. H. Yang. 2014. Fast motion estimation based on confidence interval. IEEE Transactions on Circuits and Systems for Video Technology 24, 8, 1310--1322. DOI:http://dx.doi.org/10.1109/TCSVT.2014.2306035 Google ScholarGoogle ScholarCross RefCross Ref
  9. T. K. Lee, Y. L. Chan, and W. C. Siu. 2014. Depth-based adaptive search range algorithm for motion estimation in HEVC. In 19th International Conference on Digital Signal Processing (ICDSP’14). 919--923. DOI:http://dx.doi.org/10.1109/ICDSP.2014.6900803 Google ScholarGoogle ScholarCross RefCross Ref
  10. H. Li, Y. Zhang, and H. Chao. 2013. An optimally scalable and cost-effective fractional-pixel motion estimation algorithm for HEVC. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP’13). 1399--1403. DOI:http://dx.doi.org/10.1109/ICASSP.2013.6637881 Google ScholarGoogle ScholarCross RefCross Ref
  11. X. Li, R. Wang, X. Cui, and W. Wang. 2015. Context-adaptive fast motion estimation of HEVC. In IEEE International Symposium on Circuits and Systems (ISCAS’15). 2784--2787. DOI:http://dx.doi.org/10.1109/ISCAS.2015.7169264 Google ScholarGoogle ScholarCross RefCross Ref
  12. Z. Pan, P. Jin, J. Lei, Y. Zhang, X. Sun, and S. Kwong. 2016. Fast reference frame selection based on content similarity for low complexity HEVC encoder. Journal of Visual Communication and Image Representation 40, Part B, 516--524.Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Z. Pan, S. Kwong, M. T. Sun, and J. Lei. 2014. Early MERGE mode decision based on motion estimation and hierarchical depth correlation for HEVC. IEEE Transactions on Broadcasting 60, 2, 405--412. DOI:http://dx.doi.org/10.1109/TBC.2014.2321682 Google ScholarGoogle ScholarCross RefCross Ref
  14. Z. Pan, J. Lei, Y. Zhang, X. Sun, and S. Kwong. 2016. Fast motion estimation based on content property for low-complexity H.265/HEVC encoder. IEEE Transactions on Broadcasting 62, 3, 675--684. DOI:http://dx.doi.org/10.1109/TBC.2016.2580920 Google ScholarGoogle ScholarCross RefCross Ref
  15. Z. Pan, Y. Zhang, and S. Kwong. 2015. Efficient motion and disparity estimation optimization for low complexity multiview video coding. IEEE Transactions on Broadcasting 61, 2, 166--176. DOI:http://dx.doi.org/10.1109/TBC.2015.2419824 Google ScholarGoogle ScholarCross RefCross Ref
  16. L. Shen, P. An, Z. Zhang, Q. Hu, and Z. Chen. 2015. A 3D-HEVC fast mode decision algorithm for real-time applications. ACM Transactions on Multimedia Computing, Communications, and Applications 11, 3, Article 34, 23 pages. DOI:http://dx.doi.org/10.1145/2700298 Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. T. Sotetsumoto, T. Song, and T. Shimamoto. 2013. Low complexity algorithm for sub-pixel motion estimation of HEVC. In IEEE International Conference on Signal Processing, Communication and Computing (ICSPCC’13). 1--4. DOI:http://dx.doi.org/10.1109/ICSPCC.2013.6664018 Google ScholarGoogle ScholarCross RefCross Ref
  18. G. J. Sullivan, J. R. Ohm, W. J. Han, and T. Wiegand. 2012. Overview of the high efficiency video coding (HEVC) standard. IEEE Transactions on Circuits and Systems for Video Technology 22, 12, 1649--1668. DOI:http://dx.doi.org/10.1109/TCSVT.2012.2221191 Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. C. Yan, Y. Zhang, J. Xu, F. Dai, L. Li, Q. Dai, and F. Wu. 2014a. A highly parallel framework for HEVC coding unit partitioning tree decision on many-core processors. IEEE Signal Processing Letters 21, 5, 573--576. DOI:http://dx.doi.org/10.1109/LSP.2014.2310494 Google ScholarGoogle ScholarCross RefCross Ref
  20. C. Yan, Y. Zhang, J. Xu, F. Dai, J. Zhang, Q. Dai, and F. Wu. 2014b. Efficient parallel framework for HEVC motion estimation on many-core processors. IEEE Transactions on Circuits and Systems for Video Technology 24, 12, 2077--2089. DOI:http://dx.doi.org/10.1109/TCSVT.2014.2335852 Google ScholarGoogle ScholarCross RefCross Ref
  21. S. Yang, H. J. Shim, and B. Jeon. 2014. Motion vector inheritance method for fast HEVC encoding. In IEEE International Symposium on Broadband Multimedia Systems and Broadcasting. 1--4. DOI:http://dx.doi.org/10.1109/BMSB.2014.6873512 Google ScholarGoogle ScholarCross RefCross Ref
  22. X. Zuo and L. Yu. 2015. A novel interpolation-free scheme for fractional pixel motion estimation. In Picture Coding Symposium (PCS’15). 80--84. DOI:http://dx.doi.org/10.1109/PCS.2015.7170051 Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Adaptive Fractional-Pixel Motion Estimation Skipped Algorithm for Efficient HEVC Motion Estimation

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in

    Full Access

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader
    About Cookies On This Site

    We use cookies to ensure that we give you the best experience on our website.

    Learn more

    Got it!