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Mode Skipping for HEVC Screen Content Coding via Random Forest

模式为经由随机的福雷斯特编码的 HEVC 屏幕内容跳过

作     者:Tsang, Sik-Ho Chan, Yui-Lam Kuang, Wei 

作者机构:Hong Kong Polytech Univ Dept Elect & Informat Engn Hung Hom Hong Kong Peoples R China 

出 版 物:《IEEE TRANSACTIONS ON MULTIMEDIA》 (IEEE多媒体汇刊)

年 卷 期:2019年第21卷第10期

页      面:2433-2446页

核心收录:

学科分类:0810[工学-信息与通信工程] 0808[工学-电气工程] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术(可授工学、理学学位)] 

基  金:Hong Kong Research Grants Council [PolyU 152112/17E] 

主  题:HEVC machine learning random forest screen content coding video coding 

摘      要:Screen content coding (SCC) is the extension to high-efficiency video coding (HEVC) for compressing screen content videos. New coding tools, intrablock copy (IBC), and palette (PLT) modes, are introduced to encode screen content (SC) such as texts and graphics. The IBC mode is used for encoding repeating patterns by performing block matching within the same frame, while the PLT mode is designed for SC with few distinct colors by coding the major colors and their corresponding locations using an index map. However, the use of IBC and PLT modes increases the encoder complexity remarkably though coding efficiency can be improved. Therefore, we propose to have a mode skipping approach to reduce the encoder complexity of SCC by making use of SC characteristics, neighbor coding unit (CU) correlations, and intermediate cost information via random forest (RF). Detailed feature analyses and sample preparation are also described. A novel hyperparameter tuning approach with the consideration of coding bitrate and encoding time is proposed for RFs at each CU size to further boost the encoding process. Experimental results show that our proposed approach can obtain 45.06% average encoding time reduction with only a 1.08% increase in Bjontegaard delta bitrate. Average encoding time can even be reduced to 58.57% by regulating the hyperparameters.

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