Abstract
The brute force rate-distortion optimisation based approach used in the High Efficiency Video Coding(HEVC) encoders to determine the best block partitioning structure for a given content demands an excessive amount of computational resources. In this context, this paper proposes a novel algorithm to reduce the computational complexity of HEVC inter-prediction using Support Vector Machines. The proposed algorithm predicts the Coding Unit (CU) split decision of a particular block enabling the encoder to directly encode the selected block, avoiding the unnecessary evaluation of the remaining CU size combinations. Experimental results demonstrate encoding time reductions of ~58% ~50%2.27%1.89% Bjøntegaard Delta Bit Rate (BDBR) losses for Random Access and Low-Delay B configurations, respectively.
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@inproceedings{8903081,
title = {Fast CU Size Decisions for HEVC Inter-Prediction Using Support Vector Machines},
author = {Buddhiprabha Erabadda and Thanuja Mallikarachchi and Gosala Kulupana and Anil Fernando},
doi = {10.23919/EUSIPCO.2019.8903081},
issn = {2076-1465},
year = {2019},
date = {2019-09-01},
booktitle = {2019 27th European Signal Processing Conference (EUSIPCO)},
pages = {1-5},
abstract = {The brute force rate-distortion optimisation based approach used in the High Efficiency Video Coding(HEVC) encoders to determine the best block partitioning structure for a given content demands an excessive amount of computational resources. In this context, this paper proposes a novel algorithm to reduce the computational complexity of HEVC inter-prediction using Support Vector Machines. The proposed algorithm predicts the Coding Unit (CU) split decision of a particular block enabling the encoder to directly encode the selected block, avoiding the unnecessary evaluation of the remaining CU size combinations. Experimental results demonstrate encoding time reductions of ~58% ~50%2.27%1.89% Bjøntegaard Delta Bit Rate (BDBR) losses for Random Access and Low-Delay B configurations, respectively.},
keywords = {Coding Unit (CU), encoding complexity reduction, HEVC, interprediction, Support Vector Machine (SVM), University of Surrey},
pubstate = {published},
tppubtype = {inproceedings}
}