Flexible Motion Vector Resolution Prediction for Video Coding

The latest video coding standard, High Efficiency Video Coding (HEVC), uses quarter-pixel motion vector (MV) resolution for motion compensation. The adaptation of MV resolution supported by progressive MV resolution (PMVR) brings further improvement to performance by progressively adjusting the reso...

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Bibliographic Details
Published in:IEEE transactions on circuits and systems for video technology Vol. 29; no. 11; pp. 3302 - 3316
Main Authors: Ray, Bappaditya, Larabi, Mohamed-Chaker, Jung, Joel
Format: Journal Article
Language:English
Published: New York IEEE 01.11.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Institute of Electrical and Electronics Engineers
Subjects:
Adaptation
Coding
Coding standards
Complexity theory
Delay
Encoding
Energy resolution
Engineering Sciences
HEVC
Motion compensation
Motion simulation
Motion vector resolution
progressive MV resolution
Random access
Signal and Image processing
Signal resolution
Spatiotemporal phenomena
Video coding
Video compression
Motion vector resolution
Progressive MV resolution
HEVC
ISSN:1051-8215, 1558-2205
Online Access:Get full text
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Summary:The latest video coding standard, High Efficiency Video Coding (HEVC), uses quarter-pixel motion vector (MV) resolution for motion compensation. The adaptation of MV resolution supported by progressive MV resolution (PMVR) brings further improvement to performance by progressively adjusting the resolution according to the distance between the MV and its predictor. However, progressive adjustment of resolution by PMVR does not consider the inherent characteristics of the coding block. In this paper, we propose several ways to improve PMVR. First, we show that the performance of PMVR is correlated with the spatiotemporal characteristics of the video sequence. Then, to cope with the limitations of PMVR, we propose a flexible framework for the adaptation of MV resolution using: 1) PU size and gradient; 2) PU size, gradient, and MV components; and 3) PU size and spatiotemporal characteristics of the frames. Finally, a smart motion estimation around multiple MV predictors is performed to take full advantage of the proposed scheme. The proposed tools are implemented on top of HM-16.6. Extensive experiments and comparison with HEVC show 1.3%, 2.7%, and 1.0% average BD-Rate savings for random access, low-delay P, and low-delay B configurations, respectively.
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ISSN:1051-8215
1558-2205
DOI:10.1109/TCSVT.2018.2878401