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Journal of Real-Time Image Processing

, Volume 15, Issue 1, pp 3–12 | Cite as

A low energy adaptive motion estimation hardware for H.264 multiview video coding

  • Yusuf Aksehir
  • Kamil Erdayandi
  • Tevfik Zafer Ozcan
  • Ilker HamzaogluEmail author
Special Issue Paper

Abstract

Multiview video coding (MVC) is the process of efficiently compressing stereo (two views) or multiview video signals. The improved compression efficiency achieved by H.264 MVC comes with a significant increase in computational complexity. Temporal prediction and inter-view prediction are the most computationally intensive parts of H.264 MVC. Therefore, in this paper, we propose novel techniques for reducing the amount of computations performed by temporal and inter-view predictions in H.264 MVC. The proposed techniques reduce the amount of computations performed by temporal and inter-view predictions significantly with very small PSNR loss and bit rate increase. We also propose a low energy adaptive H.264 MVC motion estimation hardware for implementing the temporal and inter-view predictions including the proposed computation reduction techniques. The proposed hardware is implemented in Verilog HDL and mapped to a Xilinx Virtex-6 FPGA. The FPGA implementation is capable of processing 30 × 8 = 240 frames per second (fps) of CIF (352 × 288) size eight view video sequence or 30 × 2 = 60 fps of VGA (640 × 480) size stereo (two views) video sequence. The proposed techniques reduce the energy consumption of this hardware significantly.

Keywords

H.264 Multiview video coding Motion estimation Hardware implementation FPGA 

Notes

Acknowledgments

This research was supported in part by the Scientific and Technological Research Council of Turkey (TUBITAK) under the contract 111E013.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Yusuf Aksehir
    • 1
  • Kamil Erdayandi
    • 1
  • Tevfik Zafer Ozcan
    • 1
  • Ilker Hamzaoglu
    • 1
    Email author
  1. 1.Faculty of Engineering and Natural SciencesSabanci UniversityIstanbulTurkey

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