Research Article
Fast Inter Prediction Mode Decision Algorithm Based on Data Mining
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@INPROCEEDINGS{10.1007/978-3-030-00557-3_10, author={Tengrui Shi and Xiaobo Guo and Daihui Mo and Jian Wang}, title={Fast Inter Prediction Mode Decision Algorithm Based on Data Mining}, proceedings={Machine Learning and Intelligent Communications. Third International Conference, MLICOM 2018, Hangzhou, China, July 6-8, 2018, Proceedings}, proceedings_a={MLICOM}, year={2018}, month={10}, keywords={HEVC Inter prediction Data mining Decision trees}, doi={10.1007/978-3-030-00557-3_10} }- Tengrui Shi
Xiaobo Guo
Daihui Mo
Jian Wang
Year: 2018
Fast Inter Prediction Mode Decision Algorithm Based on Data Mining
MLICOM
Springer
DOI: 10.1007/978-3-030-00557-3_10
Abstract
The HEVC greatly improves coding efficiency. However, this is accompanied by an increase in the complexity of the coding calculation, which is higher than H.264. We find that there are several features that are highly correlated with the CU’s best split decision in inter prediction. As a result, we choose decision trees to solve the splitting decision problem. We implement the decision trees on official software HM16.2 and test the algorithm on the testing set. Experiments indicate that the fast decision algorithm improve the coding performance more efficiently than some existing algorithms.
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