Fast multiresolution motion vector estimation for video coding by using spatial correlation

1995 ◽  
Author(s):  
Junavit Chalidabhongse ◽  
Sungook Kim ◽  
C.-C. Jay Kuo
Keyword(s):  
Video Coding ◽  
Spatial Correlation ◽  
Motion Vector ◽  
Vector Estimation

Spatial correlation-based approach to motion vector estimation in video coding

1995 ◽  
Author(s):  
Junavit Chalidabhongse ◽  
Sungook Kim ◽  
C.-C. Jay Kuo
Keyword(s):  
Video Coding ◽  
Spatial Correlation ◽  
Motion Vector ◽  
Vector Estimation

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.

An Improved Error Concealment Technique Based on Multi-View Video Coding

2014 ◽  
Vol 599-601 ◽  
pp. 1383-1386
Author(s):  
Hai Bo Liu ◽  
Xiao Sheng Huang
Keyword(s):  
Image Reconstruction ◽  
Video Coding ◽  
Spatial Correlation ◽  
Error Concealment ◽  
Motion Vector ◽  
Temporal Correlation ◽  
Experimental Results ◽  
Matching Algorithm ◽  
Video Images ◽  
Disparity Vector

In this paper, we propose a improved error concealment technique based on multi-view video coding to recover damaged video images. At first,It uses BMA(Boundary Matching Algorithm) method to recover the lost or erroneously received motion vector or disparity vector,then combining inter-view correlation, temporal correlation and spatial correlation to recover the lost blocks. The JM12.0 model of H.264 standard is used to evaluate the algorithm. And the experimental results show that our algorithm achieved a better image reconstruction.

Motion vector estimation using spatiotemporal prediction and its application to video coding

1996 ◽  
Author(s):  
Robert M. Armitano ◽  
Ronald W. Schafer ◽  
Frederick L. Kitson ◽  
Bhaskaran Vasudev
Keyword(s):  
Video Coding ◽  
Motion Vector ◽  
Vector Estimation
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