Probability Model Estimation for M-Ary Random Variables
Jingning Han, Yaowu Xu · 2022 IEEE International Conference on Image Processing (ICIP) · 2022
The entropy coding system in AV1 processes syntax elements as M-ary random variables. In comparison to the binarization approach used in its predecessor VP9 that converts an M-ary random variables into a series of binary symbols for entropy coding, the M-ary random variable approach provides higher throughput for hardware decoders. The non-binary probability table associated with the M-ary random variable, however, poses new challenges in the probability model estimation process beyond the binary case. This paper provides a retrospect of the probability model estimation for M-ary random variables used in AV1, and proposes new algorithms for the probability estimation process to improve the compression efficiency. Its efficacy is experimentally demonstrated under various testing conditions.