Machine Learning-Based Coding Unit Depth Decisions for Flexible Complexity Allocation in High Efficiency Video Coding

@article{Zhang2015MachineLC,
  title={Machine Learning-Based Coding Unit Depth Decisions for Flexible Complexity Allocation in High Efficiency Video Coding},
  author={Yun Zhang and Sam Kwong and Xu Wang and Hui Yuan and Zhaoqing Pan and Long Xu},
  journal={IEEE Transactions on Image Processing},
  year={2015},
  volume={24},
  pages={2225-2238}
}
In this paper, we propose a machine learning-based fast coding unit (CU) depth decision method for High Efficiency Video Coding (HEVC), which optimizes the complexity allocation at CU level with given rate-distortion (RD) cost constraints. First, we analyze quad-tree CU depth decision process in HEVC and model it as a three-level of hierarchical binary decision problem. Second, a flexible CU depth decision structure is presented, which allows the performances of each CU depth decision be… CONTINUE READING
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