Fast transcoding of DVC-HEVC based on naive Bayes classification
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    Abstract:

    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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华 玲,唐 韬,卿粼波,何小海,荣 松.基于朴素贝叶斯分类的DVC-HEVC快速转码[J]. Journal of Terahertz Science and Electronic Information Technology ,2020,18(2):235~240

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History
  • Received:January 29,2019
  • Revised:April 11,2019
  • Adopted:
  • Online: May 07,2020
  • Published: