Context-based adaptive binary arithmetic coding (CABAC) is a highly efficient entropy coding way

but its coding speed is restricted by high computational complexity

which becomes a major bottleneck in its application To solve this problem

an effective way

based on the analysis of the CABAC algorithm and its computational complexity

will be proposed in this article to improve the algorithms coding speed by improving the probability estimation update part The algorithm first codes packets which each include N symbols

and then updates the probability estimation part

which decreases the update frequency of probability estimation remarkably The experimental results show that

compared with the former algorithms

the coding speed of CABAC has been substantially increased from 133% to 307%

with coding efficiency declines a little from 187% to 298%