OpenCL based high-quality HEVC motion estimation on GPU

Fan Wang, Dajiang Zhou, Satoshi Goto

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    12 Citations (Scopus)


    This paper presents a high quality H.265/HEVC motion estimation implementation with the cooperation of CPU and GPU. The data dependency from MVP (Motion Vector Predictor) restricts the degree of parallelism on GPU. To overcome the constraint from MVP, we propose to use an estimated MVP on GPU and the accurate MVP to refine the motion vector on CPU. GPU fully utilizes its tremendous parallel computing ability without the restriction from MVP. CPU makes up for the deviation from GPU with a small range refinement. Encoding speed benefits from the high degree of parallelism and compression performance is maintained by the CPU refinement. Experimental result shows that the speedup achieves 2.39 times and 32.77 times in the whole ×265 encoder with CPU SIMD (Single Instruction Multiple Data) on and off, respectively. On the other hand, the quality degradation is negligible with only 0.05% increase of BD-rate.

    Original languageEnglish
    Title of host publication2014 IEEE International Conference on Image Processing, ICIP 2014
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Number of pages5
    ISBN (Electronic)9781479957514
    Publication statusPublished - 2014 Jan 28


    • GPU
    • H.265
    • HEVC
    • motion estimation
    • parallel computing

    ASJC Scopus subject areas

    • Computer Vision and Pattern Recognition


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