The Improved Full Search Algorithm for Motion Estimation with GPU Accelection

DOI

10.2991/ceis-16.2016.47How to use a DOI?

Keywords

motion estimation; block matching; full search; spatial and temporal correlation; parallel computing

Abstract

Robust motion vector estimation algorithm plays an important role in video processing. Block matching algorithm for motion estimation as a mature search technique has been widely used in video applications because of its simplicity and easy implement. To increase the accuracy of motion vector prediction, an improved motion estimation algorithm is proposed that combines full search algorithm with spatial and temporal correlation. To further reduce the computational cost, a powerful parallel algorithm based on GPU is designed by using a series of optimization methods. Experimental results show that the proposed method gives the high PSNRs by testing the video sequences and the computation speed of the optimized algorithm is greatly improved.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zhuo Liu
AU  - Yi-Nan Lu
AU  - Tao Liu
AU  - Tian-Wen Yuan
PY  - 2016/11
DA  - 2016/11
TI  - The Improved Full Search Algorithm for Motion Estimation with GPU Accelection
BT  - Proceedings of the 2016 International Conference on Computer Engineering and Information Systems
PB  - Atlantis Press
SP  - 241
EP  - 244
SN  - 2352-538X
UR  - https://doi.org/10.2991/ceis-16.2016.47
DO  - 10.2991/ceis-16.2016.47
ID  - Liu2016/11
ER  -