Journal of Terahertz Science and Electronic Information Technology , Volume. 18, Issue 2, 235(2020)

Fast transcoding of DVC-HEVC based on naive Bayes classification

HUA Ling1, TANG Tao2, QING Linbo1、*, HE Xiaohai1, and RONG Song3
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    The transcoding between Distributed Video Coding(DVC) and traditional video provides an effective way to realize low-power video communication between mobile terminal devices. In this paper, DVC and HEVC(High Efficiency Video Coding) transcoding is taken as the research object, and the decoding end information of DVC is utilized to carry out complexity optimization research on the division process of coding unit with high complexity in HEVC. Firstly, texture complexity, motion vector and prediction residuals related to Coding Unit(CU) partition are extracted from DVC decoder. Then, based on naive Bayes principle, a CU fast partition model is established at the HEVC coding end. After the model is generated, current CU division can be quickly determined by inputting feature information, avoiding a cost calculation process of large number of Rate Distortion(RD). Experimental results show that the proposed scheme significantly reduces the HEVC coding time by 58.26% with a slight increase in the encoding bit rate, and hardly affects the quality of video.

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    HUA Ling, TANG Tao, QING Linbo, HE Xiaohai, RONG Song. Fast transcoding of DVC-HEVC based on naive Bayes classification[J]. Journal of Terahertz Science and Electronic Information Technology , 2020, 18(2): 235

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    Paper Information

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    Received: Jan. 29, 2019

    Accepted: --

    Published Online: May. 28, 2020

    The Author Email: Linbo QING (qing_lb@scu.edu.cn)

    DOI:10.11805/tkyda2018341

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