An Accelerated H.264/AVC Encoder on Graphic Processing Unit for UAV Videos

  • Yih-Chuan LinEmail author
  • Shang-Che Wu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10149)


With regards to the nature of high intensive computation for motion estimation with an H.264/AVC encoder, this paper presents a parallel block-matching algorithm implemented on a general purpose graphics processing units (GPU) to speed up the execution of UAV video coding. Traditional parallel block-matching algorithms are primarily used to leverage the huge number of computational cores in graphic processing units, which can be used to compute the block-matching operation at each candidate position in a search range by an independent thread of kernel computation. In realistic scenarios, the time used to transfer pixel values among the various memory modules to fulfill the operation in a GPU system is much higher than the computation time used for computing each block-matching operation by the kernel threads. This leads to a performance improvement bottleneck for GPU algorithm design. The proposed algorithm exploits the characteristics of distinct memory modules on the data transfer speed for the block-matching algorithm and proposes a feasible mechanism to reduce the bandwidth of data transmission required for the parallel block-matching algorithms implemented on GPU system. With experiments on GPU systems, the proposed parallel block-matching algorithm gains up to 99% execution reduction of motion estimation compared to the host processor only motion estimation process.


Unmanned aerial vehicle Aerial video coding GPU Motion estimation H.264/AVC 


  1. 1.
    Chen, B.-Y., Yang, S.-H.: Using H.264 coded block patterns for fast inter-mode selection, In: IEEE International Conference on Multimedia and Expo, pp. 721–724. Hannover (2008)Google Scholar
  2. 2.
    Chen, W.-N., Hang, H.-M.: H.264/AVC motion estimation implementation on compute unified device architecture (CUDA). In: IEEE International Conference on Multimedia and Expo (ICME), pp. 697–700 (2008)Google Scholar
  3. 3.
    Colic, A., Kalva, H., Furht, B.: Exploring NVIDIA-CUDA for video coding. In: Proceedings of the First Annual ACM SIGMM Conference on Multimedia systems, pp. 13–22. Phoenix, Arizona, USA (2010)Google Scholar
  4. 4.
    Colomina, I., Molina, P.: Unmanned aerial systems for photogrammetry and remote sensing: a review. ISPRS J. Photogramm. Remote Sens. 92, 79–97 (2014)CrossRefGoogle Scholar
  5. 5.
    Free HD Stock Footage.
  6. 6.
    H.264/AVC Reference Software 19.0.
  7. 7.
    Lin, Y.C, Wu, S.C.: Parallel motion estimation and GPU-based fast coding unit splitting mechanism for HEVC. In: IEEE High Performance and Extreme Computing Conference (HPEC 2016), Boston, USA, 13–15 September 2016Google Scholar
  8. 8.
    Moriyoshi, T., Takano, F., Nakamura, Y.: GPU acceleration of H.264/MPEG-4 AVC software video encoder. In: Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA), Xi’an, China (2011)Google Scholar
  9. 9.
  10. 10.
    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), 1649–1668 (2013)CrossRefGoogle Scholar
  11. 11.
  12. 12.
    Wiegand, T., Sullivan, G.J., Bjøntegaard, G., Luthra, A.: Overview of the H.264/AVC video coding standard. IEEE Trans. Circuits Syst. Video Technol. 13(7), 560–576 (2003)CrossRefGoogle Scholar
  13. 13.
    Yang, F., Ma, H.: Aerial video encoding optimization based on x264. Open J. Appl. Sci. 3(1B), 36–40 (2013)CrossRefGoogle Scholar
  14. 14.
    Yang, J., Chen, Y.: A novel fast inter-mode decision algorithm for H.264/AVC based on motion estimation residual. In: WASE International Conference on Information Engineering (ICIE), vol. 1, pp. 153–156, Taiyuan, Shanxi (2009)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Computer Science and Information EngineeringNational Formosa UniversityYunlinTaiwan

Personalised recommendations