Fast Motion Estimation Based on Content Property for Low-Complexity H.265/HEVC Encoder

Abstract

The high definition (HD) and ultra HD videos can be widely applied in broadcasting applications. However, with the increased resolution of video, the volume of the raw HD visual information data increases significantly, which becomes a challenge for storage, processing, and transmitting the HD visual data. The state-of-the-art video compression standardH.265/High Efficiency Video Coding (HEVC) compresses the raw HD visual data efficiently, while the high compression rate comes at the cost of heavy computation load. Hence, reducing the encoding complexity becomes vital for the H.265/HEVC encoder to be used in broadcasting applications. In this paper, based on the best motion vector selection correlation among the different size prediction modes, we propose a fast motion estimation (ME) method to reduce the encoding complexity of the H.265/HEVC encoder. First, according to the prediction unit (PU) partition type, all PUs are classified into two classes, parent PU and children PUs, respectively. Then, based on the best motion vector selection correlation between the parent PU and children PUs, the block matching search process of the children PUs is adaptively skipped if their parent PU chooses the initial search point as its final optimal motion vector in the ME process. Experimental results show that the proposed method achieves an average of 20% ME time saving as compared with the original HM-TZSearch. Meanwhile, the rate distortion performance degradation is negligible. Manuscript received November 2, 2015; revised May 10, 2016; accepted June 6, 2016. This work was supported in part by the National Natural Science Foundation of China under Grant 61501246, Grant 61271324, Grant 61471348, and Grant 61232016, in part by the Natural Science Foundation of Jiangsu Province of China under Grant BK20150930, in part by the Natural Science Foundation of the Jiangsu Higher Education Institutions of China under Grant 15KJB510019, in part by the Natural Science Foundation of Hebei Province of China under Grant F2015202311, in part by the Project through the Priority Academic Program Development of Jiangsu Higher Education Institutions, in part by the Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology under Grant 2015r012; and in part by the Natural Science Foundation of Guangdong Province for Distinguished Young Scholar under Grant 2016A030306022. (Corresponding author: Jianjun Lei.) Z. Pan is with the School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044, China, also with the Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science and Technology, Nanjing 210044, China, and also with the School of Computer Science and Engineering, Hebei University of Technology, Tianjin 300401, China (e-mail: zqpan3-c@my.cityu.edu.hk). J. Lei is with the School of Electronic Information Engineering, Tianjin University, Tianjin 300072, China (e-mail: jjlei@tju.edu.cn). Y. Zhang is with the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China (e-mail: yun.zhang@siat.ac.cn). X. Sun is with the School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044, China (e-mail: xmsun2013@gmail.com). S. Kwong is with the Department of Computer Science, City University of Hong Kong, Hong Kong (e-mail: cssamk@cityu.edu.hk). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TBC.2016.2580920

DOI: 10.1109/TBC.2016.2580920
020406020162017
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@article{Pan2016FastME, title={Fast Motion Estimation Based on Content Property for Low-Complexity H.265/HEVC Encoder}, author={Zhaoqing Pan and Jianjun Lei and Yun Zhang and Xingming Sun and Sam Kwong}, journal={TBC}, year={2016}, volume={62}, pages={675-684} }