Adaptive motion estimation in video coding with a stochastic model

Author(s):  
Sungook Kim ◽  
C.-C.J. Kuo
2013 ◽  
Vol 15 (1) ◽  
pp. 3-12 ◽  
Author(s):  
Yusuf Aksehir ◽  
Kamil Erdayandi ◽  
Tevfik Zafer Ozcan ◽  
Ilker Hamzaoglu

2012 ◽  
Vol 51 (11) ◽  
pp. 117001 ◽  
Author(s):  
Hoyoung Lee ◽  
Bongsoo Jung ◽  
Jooyoung Jung ◽  
Byeungwoo Jeon

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Pengyu Liu ◽  
Yuan Gao ◽  
Kebin Jia

The unsymmetrical-cross multihexagon-grid search (UMHexagonS) is one of the best fast Motion Estimation (ME) algorithms in video encoding software. It achieves an excellent coding performance by using hybrid block matching search pattern and multiple initial search point predictors at the cost of the computational complexity of ME increased. Reducing time consuming of ME is one of the key factors to improve video coding efficiency. In this paper, we propose an adaptive motion estimation scheme to further reduce the calculation redundancy of UMHexagonS. Firstly, new motion estimation search patterns have been designed according to the statistical results of motion vector (MV) distribution information. Then, design a MV distribution prediction method, including prediction of the size of MV and the direction of MV. At last, according to the MV distribution prediction results, achieve self-adaptive subregional searching by the new estimation search patterns. Experimental results show that more than 50% of total search points are dramatically reduced compared to the UMHexagonS algorithm in JM 18.4 of H.264/AVC. As a result, the proposed algorithm scheme can save the ME time up to 20.86% while the rate-distortion performance is not compromised.


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