An Efficient Hardware-Oriented Algorithm of Spatial Motion Vector Prediction for AVS HD Video Encoder

2014 ◽  
Vol 556-562 ◽  
pp. 4365-4371
Author(s):  
Ming Hui Yang ◽  
Xiao Dong Xie
Keyword(s):  
Motion Estimation ◽  
Motion Vector ◽  
Spatial Motion ◽  
Coding Efficiency ◽  
Multi Stage ◽  
Macro Block ◽  
Optimal Coding ◽  
Adjacent Block ◽  
Left Block ◽  
Motion Vector Prediction

Motion Vector Prediction (MVP) plays an important role in improving coding efficiency in HEVC, H.264/AVC and AVS video coding standard. MVP is implemented by exploiting redundancy of adjacent-block optimal coding information under the constraint that MVP must be performed in a serial way. The constraint prevents parallel processing and MB pipeline based on LevelC+. In multi-stage pipeline, to some extent, adjacent-block best mode-decision information can hardly be obtained. In this paper, we propose a new hardware-oriented method to improve the coding performance at a cost of few hardware resources. When adjacent block is not available, spatial motion vector prediction (SMVP) for integer motion estimation (IME) and fraction motion estimation (FME) will take the IME best mode information and FME best mode information of left block as best information to derive PMV (Predicted Motion Vector) for current macro-block or block. Experimental results shows that the method we propose can achieve a better performance than the existing methods by 0.1db for the cases with intense movement and a non-degrading performance for flat cases.

scholarly journals Efficient motion vector prediction scheme for high speed motion estimation in H.264/AVC

2008 ◽  
Vol 5 (21) ◽  
pp. 889-894
Author(s):  
Jinha Choi ◽  
Wonjae Lee ◽  
Yunho Jung ◽  
Jaeseok Kim
Keyword(s):  
Motion Estimation ◽  
High Speed ◽  
Motion Vector ◽  
Prediction Scheme ◽  
Motion Vector Prediction

Improvements on Motion Estimation Algorithms in Video Coding for H.264/AVC

2013 ◽  
Vol 756-759 ◽  
pp. 3455-3460
Author(s):  
Xiao Li Wang ◽  
Long Zhao
Keyword(s):  
Motion Estimation ◽  
Video Coding ◽  
Real Time ◽  
Video Compression ◽  
Motion Vector ◽  
Coding Efficiency ◽  
Estimation Algorithms ◽  
Whole Process ◽  
Motion Activity ◽  
Precision Motion

Motion estimation is the most important step in video compression. By using high precision motion vector in the H.264 encoder, the calculation is rapidly increased, but in the whole process of coding, motion estimation occupies about 80%. Although many motion estimation algorithms have been proposed to reduce the computational complexity of motion estimation, it still cannot meet the strict real-time demand. In this paper, based on the analysis of UMHexagonS algorithm, dynamic searching window is chosen in the UMHexagonS algorithm, then according to the motion activity, it uses different template to reduce the motion estimation time and improve video coding efficiency. Proved by the experiments on various test sequences, compared with the UMHexagonS algorithm, the motion estimation time of the proposed algorithm average saves 17.7525% in the case of the quality of the reconstructed image and rate close. It not only reduces the complexity of the algorithm, but also improves the real-time performance of the encoder.

scholarly journals Spatial Correlation-Based Motion-Vector Prediction for Video-Coding Efficiency Improvement

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 129 ◽  
Author(s):  
Xiantao Jiang ◽  
Tian Song ◽  
Takafumi Katayama ◽  
Jenq-Shiou Leu
Keyword(s):  
Video Coding ◽  
Spatial Correlation ◽  
Video Quality ◽  
Motion Vector ◽  
Prediction Algorithm ◽  
Computation Complexity ◽  
Coding Efficiency ◽  
Depth Prediction ◽  
Motion Vector Prediction ◽  
Coding Unit

H.265/HEVC achieves an average bitrate reduction of 50% for fixed video quality compared with the H.264/AVC standard, while computation complexity is significantly increased. The purpose of this work is to improve coding efficiency for the next-generation video-coding standards. Therefore, by developing a novel spatial neighborhood subset, efficient spatial correlation-based motion vector prediction (MVP) with the coding-unit (CU) depth-prediction algorithm is proposed to improve coding efficiency. Firstly, by exploiting the reliability of neighboring candidate motion vectors (MVs), the spatial-candidate MVs are used to determine the optimized MVP for motion-data coding. Secondly, the spatial correlation-based coding-unit depth-prediction is presented to achieve a better trade-off between coding efficiency and computation complexity for interprediction. This approach can satisfy an extreme requirement of high coding efficiency with not-high requirements for real-time processing. The simulation results demonstrate that overall bitrates can be reduced, on average, by 5.35%, up to 9.89% compared with H.265/HEVC reference software in terms of the Bjontegaard Metric.

Sign in / Sign up

Export Citation Format

Share Document