DCT-Based Residual Network For Nir Image Colorization
Hongcheng Jiang, Paras Maharjan, Zhu Li, George York
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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.