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Published on: June 8, 2022
Fast decision mechanism for ternary tree partitioning in VVC intra coding
Jiamin Sun1,2, Zhongjie Zhu1,2, Renwei Tu1
1Key Laboratory of Industrial Vision and Industrial Intelligence, Zhejiang Wanli University, Ningbo, China.
This study introduces a fast decision mechanism for Versatile Video Coding (VVC) to optimize ternary tree (TT) partitioning. The method uses image features to predict optimal patterns, significantly speeding up encoding while maintaining quality.
Area of Science:
- Video compression technology
- Digital image processing
- Machine learning for video coding
Background:
- Versatile Video Coding (VVC) relies on complex coding unit (CU) partitioning for efficiency.
- Ternary tree (TT) partitioning in VVC intra coding is computationally intensive due to rate-distortion cost calculations.
- Current methods for optimal CU partition selection are time-consuming, hindering real-time applications.
Purpose of the Study:
- To develop a fast decision mechanism for VVC's ternary tree (TT) partitioning in intra coding.
- To reduce the computational complexity associated with rate-distortion optimization (RDO) for CU partitioning.
- To enhance overall video encoding efficiency without compromising visual quality.
Main Methods:
- Investigated the correlation between image structural features and TT partition patterns.
- Developed an efficient scheme for feature representation and extraction to minimize computational load.
- Constructed comprehensive datasets for training a predictive model for optimal TT partition selection.
- Integrated a predictive model into the VVC Test Model (VTM) for pre-RDO feature analysis.
Main Results:
- The proposed mechanism effectively predicts optimal TT partition patterns, enabling bypass of complex RDO calculations.
- Experimental results show significant time-saving improvements compared to existing lightweight neural network algorithms.
- The method achieved a favorable trade-off between prediction accuracy and model complexity.
- Coding quality was preserved while substantially accelerating the video coding process.
Conclusions:
- The image feature-based decision mechanism offers a computationally efficient approach to VVC intra coding.
- This method significantly accelerates video encoding by intelligently skipping unnecessary TT partitioning computations.
- The approach demonstrates superior performance in time-saving metrics and Bjøntegaard Delta Bit Rate (BDBR) compared to prior lightweight methods.
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