The Improved Full Search Algorithm for Motion Estimation with GPU Accelection
Zhuo Liu, Yi-Nan Lu, Tao Liu, Tian-Wen Yuan
Available Online November 2016.
- https://doi.org/10.2991/ceis-16.2016.47How to use a DOI?
- motion estimation; block matching; full search; spatial and temporal correlation; parallel computing
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - 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 - https://doi.org/10.2991/ceis-16.2016.47 ID - Liu2016/11 ER -