Signal, Image and Video Processing

, Volume 9, Issue 8, pp 1805–1814 | Cite as

A high-efficient tables memory access saving algorithm for CAVLC decoding

  • Jianhua WangEmail author
  • Lianglun Cheng
  • Jun Liu
  • YunLong Sun
Original Paper


Frequent table look-up can result in high memory access, and high memory access can cause increased power consumption in CAVLC decoding. Aiming to solve the problem of high table memory access during the process of CAVLC decoding for H.264/AVC due to frequent table look-up, thereby reducing the power consumption, a high-efficient table memory access saving algorithm is presented in this paper. The contribution of the proposed scheme is that we use program code to instead of the conventional table look-up method that requires a lot of memory access. In our scheme, we use program code to realize fully the expression of all the UVLT (Unstructured Variable Length Tables) in CAVLC decoding, as a result, all the decoded codewords in UVLT can be obtained easily through a program execution way instead of sequential table look-up. which can save a lot of memory access and power consumption due to without looking up UVLT in CAVLC decoding, The simulation results show that our proposed scheme can save 100 % memory access of table look-up for CAVLC decoding compared with TLSS method due to the use of program code, thereby saving much power consumption, without degrading video quality.


CAVLC decoding Table look-up Memory access Program code 



The authors would like to thank the anonymous reviewers for their constructive opinions in improving this paper. The work was supported by the Joint Funds of the National Natural Science Foundation of China (No.U2012A002D01); The Strategic Emerging Industries Special of Guangdong Province (No.2012A09100013-2012BAF11B04–5150);Project of Ministry of Science and Technology (NO.2012BAF11B04); Foundation for Distinguished Young Talents in Higher Education of Guangdong (LYM11057); Doctoral Project for Natural Science Foundation of Guangdong (S2012040006666).


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Copyright information

© Springer-Verlag London 2014

Authors and Affiliations

  • Jianhua Wang
    • 1
    Email author
  • Lianglun Cheng
    • 1
  • Jun Liu
    • 1
  • YunLong Sun
    • 2
  1. 1.Faculty of AutomationGuangdong University of TechnologyGuangzhouChina
  2. 2.Faculty of Information EngineeringGuangdong University of TechnologyGuangzhouChina

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