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    A Highly Parallel SAD Architecture for Motion Estimation in HEVC Encoder

    Medhat, Ahmed; Shalaby, Ahmed; Sayed, Mohammed S.; Elsabrouty, Maha; Madipour, Farhad

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    Date
    2014-11
    Citation:
    Medhat, A., Shalaby, A., Sayed, M. S., Elsabrouty, M. , Mehdipour, F. (2014, November). A Highly Parallel SAD Architecture for Motion Estimation in HEVC Encoder. IEEE Xplore (Ed.), 2014 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS) (pp.280-283). 10.1109/APCCAS.2014.7032774.
    Permanent link to Research Bank record:
    https://hdl.handle.net/10652/3813
    Abstract
    The high computational cost of the motion estimation module in the new HEVC standard raises the need for efficient hardware architectures that can meet the real-time processing constraint. In addition, targeting HD and UHD resolutions increases the motion estimation processing cost beyond the capabilities of the currently existing architectures. This paper presents a highly parallel sum of absolute difference (SAD) architecture for motion estimation in HEVC encoder. The proposed architecture has 64 PUs operating in parallel to calculate the SAD values of the prediction blocks. It processes block sizes from 4x4 up to 64x64. The proposed architecture has been prototyped, simulated and synthesized on Xilinx Virtix-7 XC7VX550T FPGA. At 458 MHz clock frequency, the proposed architecture processes 30 2K resolution fps with ±20 pixels search range. The prototyped architecture utilizes 7% of the LUTs and 5% of the slice registers in Xilinx Virtex-7 XC7VX550T FPGA.
    Keywords:
    HEVC encoder, inter prediction, SAD architecture, variable block size motion estimation (VBSME)
    ANZSRC Field of Research:
    080309 Software Engineering
    Available Online at:
    http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7032774
    Rights:
    This digital work is protected by copyright. It may be consulted by you, provided you comply with the provisions of the Act and the following conditions of use: Any use you make of these documents or images must be for research or private study purposes only, and you may not make them available to any other person. You will recognise the author's and publishers rights and give due acknowledgement where appropriate.
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