TY - GEN
T1 - Fast Coding Unit Decision for Intra Screen Content Coding Based on Ensemble Learning
AU - Xue, Yali
AU - Wang, Xu
AU - Zhu, Linwei
AU - Pan, Zhaoqing
AU - Kwong, Sam
PY - 2019
Y1 - 2019
N2 - The Screen Content Coding (SCC) is an extension of High Efficiency Video Coding (HEVC), and it achieves significant improvement on compression ratio. However, the obtained coding efficiency is at the cost of high computational complexity. In this paper, to reduce the computation complexity, we propose to use an ensemble classifier for predicting the coding unit (CU) in intra-coding. Firstly, the L1-loss based linear support vector machine (SVM) is employed as basic classifier for its simplicity. Then, a bagging scheme is applied to train the linear classifiers and boost the prediction accuracy by ensemble learning. Compared with the reference software SCM-5.0, the proposed scheme can achieve 30% complexity reduction on average with only 1.64% bit rates increase.
AB - The Screen Content Coding (SCC) is an extension of High Efficiency Video Coding (HEVC), and it achieves significant improvement on compression ratio. However, the obtained coding efficiency is at the cost of high computational complexity. In this paper, to reduce the computation complexity, we propose to use an ensemble classifier for predicting the coding unit (CU) in intra-coding. Firstly, the L1-loss based linear support vector machine (SVM) is employed as basic classifier for its simplicity. Then, a bagging scheme is applied to train the linear classifiers and boost the prediction accuracy by ensemble learning. Compared with the reference software SCM-5.0, the proposed scheme can achieve 30% complexity reduction on average with only 1.64% bit rates increase.
KW - Coding Unit Decision
KW - Ensemble Learning
KW - Intra Coding
KW - Linear Classification
KW - Screen Content Coding
UR - https://www.scopus.com/pages/publications/85069004551
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85069004551&origin=recordpage
U2 - 10.1109/ICASSP.2019.8682707
DO - 10.1109/ICASSP.2019.8682707
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781479981328
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 8543
EP - 8547
BT - 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing
PB - IEEE
T2 - 44th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2019)
Y2 - 12 May 2019 through 17 May 2019
ER -