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2019 | OriginalPaper | Chapter

Background Error Propagation Model Based RDO for Coding Surveillance and Conference Videos

Authors : Jian Xiong, Xianzhong Long, Ran Shi, Miaohui Wang, Jie Yang, Yunyi Li, Guan Gui

Published in: Advanced Hybrid Information Processing

Publisher: Springer International Publishing

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Abstract

Surveillance and conference videos have become increasingly important in our daily life, which brings a huge amount of video data. Existing coding standards were originally designed for generic video contents. The backgrounds are generally static in the surveillance and conference videos. The background coding errors will propagate to the subsequent frames in coding the videos. In this paper, a background error propagation (BEP) model based Rate Distortion Optimization (RDO) scheme in HEVC is proposed for the surveillance and conference videos. Firstly, the global RDO scheme is proposed to efficiently exploit the background error propagation. Secondly, a BEP model is studied to express the linear relationship between the distortion of the first frame and that of its subsequent frames. Based on the BEP model, enhanced frames are proposed to be coded with a small quantization parameter (QP) offset so as to improve the global performance. Thirdly, a bi-exponential decay model is proposed to investigate the variation of the error propagation ratio as the frame order increased. Based on the decay model, a periodical optimization scheme is presented by deploying the enhanced frames periodically. Experimental results show that the proposed algorithm achieves 11.15% bit-rate reductions on average under the low delay condition.

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Literature
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go back to reference Bjontegaard, G.: Calculation of average PSNR differences between RD curves. No. ITU-T SC16/Q6, VCEG-M33, Austin, USA, April 2001 Bjontegaard, G.: Calculation of average PSNR differences between RD curves. No. ITU-T SC16/Q6, VCEG-M33, Austin, USA, April 2001
9.
Metadata
Title
Background Error Propagation Model Based RDO for Coding Surveillance and Conference Videos
Authors
Jian Xiong
Xianzhong Long
Ran Shi
Miaohui Wang
Jie Yang
Yunyi Li
Guan Gui
Copyright Year
2019
DOI
https://doi.org/10.1007/978-3-030-19086-6_56

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