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AUTHOR(S):

Fatma Elzahra Sayadi, Marwa Chouchene, Haithem Bahri, Olfa Haggui, Bouraoui Ounir

 

TITLE

Improved approach for full search motion estimation on GPU

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ABSTRACT

In order to speed up video coding efficiency such as H.264/AVC and H265/HEVC, we propose in this paper a parallel approach of full search (FS) algorithm for motion estimation on Graphic Processor Unit (GPU). We implemented the traditional sequential FS algorithm for motion estimation to computing unified device architecture (CUDA) optimizing memory usage, taking full ad-vantage of the powerful parallel computing capability to speed up FS motion estimation. Experimental results show that our implementation on CUDA demonstrates substantial improvement up to 48 times than CPU counterpart available and can effectively speed up the FS for motion estimation

KEYWORDS

Full search, GPU, CUDA, Motion Estimation, shared memory, Optimization

REFERENCES

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[2] Dong Zhang, Bin Li, Jizheng Xu, and Houqiang Li, “Fast Transcoding from H. 264 AVC to HEVC,” 2012 IEEE International Conference on Multimedia and Expo (ICME), Melbourne, Australia, July 2012.

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[4] F. Dufaus and F. Moscheni, “Motion estimation techniques for digital TV: A review and a new contribution,”Proc. IEEE , vol. 83, pp. 858–876,Jun. 1995

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[7] CUDA API REFERENCE MANUAL (2012) Version 4.2

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[9] couturier, R.: 'Designing Scientific Application on GPUs’ (CRC Press, Taylor Francis Group, 2014

Cite this paper

Fatma Elzahra Sayadi, Marwa Chouchene, Haithem Bahri, Olfa Haggui, Bouraoui Ounir. (2017) Improved approach for full search motion estimation on GPU. International Journal of Computers, 2, 220-222

 

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