Advertisement

A Novel Two-Step Integer-pixel Motion Estimation Algorithm for HEVC Encoding on a GPU

  • Keji Chen
  • Jun Sun
  • Zongming GuoEmail author
  • Dachuan Zhao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10133)

Abstract

Integer-pixel Motion Estimation (IME) is one of the fundamental and time-consuming modules in encoding. In this paper, a novel two-step IME algorithm is proposed for High Efficiency Video Coding (HEVC) on a Graphic Processing Unit (GPU). First, the whole search region is roughly investigated with a predefined search pattern, which is analyzed in detail to effectively reduce the complexity. Then, the search result is further refined in the zones only around the best candidates of the first step. By dividing IME into two steps, the proposed algorithm combines the advantage of one-step algorithms in synchronization and the advantage of multiple-step algorithms in complexity. According to the experimental results, the proposed algorithm achieves up to 3.64 times speedup compared with previous representative algorithms, and the search accuracy is maintained at the same time. Since IME algorithm is independent from other modules, it is a good choice for different GPU-based encoding applications.

Keywords

High Efficiency Video Coding (HEVC) Graphics Processing Unit (GPU) Integer-pixel Motion Estimation (IME) Two-step algorithm 

Notes

Acknowledgment

This work was supported by National Natural Science Foundation of China under contract No. 61671025 and National Key Technology R&D Program of China under Grant 2015AA011605.

References

  1. 1.
    Sullivan, G.J., Ohm, J.-R., Han, W.-J., Wiegand, T.: Overview of the High Efficiency Video Coding (HEVC) standard. IEEE Trans. Circuits Syst. Video Technol. 22(12), 1648–1667 (2012)CrossRefGoogle Scholar
  2. 2.
    Wiegand, T., Sullivan, G.J., Bjntegaard, G., Luthra, A.: Overview of the H.264/AVC video coding standard. IEEE Trans. Circ. Syst. Video Technol. 13(7), 560–576 (2003)CrossRefGoogle Scholar
  3. 3.
    Sullivan, G.J., Wiegand, T.: Rate-distortion optimization for video compression. IEEE Signal Process. Mag. 15(6), 74–90 (1998)CrossRefGoogle Scholar
  4. 4.
    Chen, W.-N., Hang, H.-M.: H.264/AVC motion estimation implmentation on Compute Unified Device Architecture (CUDA). IEEE International Conference on Multimedia and Expo, pp. 697–700, June 2008Google Scholar
  5. 5.
    Rodríguez-Sánchez, R., Martínez, J.L., Fernández-Escribano, G., Claver, J.M., Sánchez, J.L.: Reducing complexity in H.264/AVC motion estimation by using a GPU. IEEE International Workshop on Multimedia Signal Processing, pp. 1–6, October 2011Google Scholar
  6. 6.
    Radicke, S., Hahn, J.-U., Wang, Q., Grecos, C.: Bi-predictive motion estimation for HEVC on a Graphics Processing Unit (GPU). IEEE Trans. Consumer Electron. 60(4), 728–736 (2014)CrossRefGoogle Scholar
  7. 7.
    Jiang, C., Nooshabadi, S.: A scalable massively parallel motion and disparity estimation scheme for multiview video coding. IEEE Trans. Circ. Syst. Video Technol. 26, 346–359 (2016)CrossRefGoogle Scholar
  8. 8.
    x265 Developers: x265 HEVC Encoder/H.265 Video Codec (2015). http://www.x265.org/
  9. 9.
    Bossen, F.: Common test conditions and software reference configurations. Document JCTVC-L1100, January 2013Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Keji Chen
    • 1
  • Jun Sun
    • 1
    • 2
  • Zongming Guo
    • 1
    • 2
    Email author
  • Dachuan Zhao
    • 3
  1. 1.Institute of Computer Science and Technology of Peking UniversityBeijingChina
  2. 2.Cooperative Medianet Innovation CenterShanghaiChina
  3. 3.Advanced Micro Devices Co., Ltd.BeijingChina

Personalised recommendations