基于统计建模的HEVC快速率失真估计算法

针对高效视频编码(HEVC)率失真优化过程中复杂的码率与失真计算,提出一种高准确性的快速率失真估计模型。该算法评估熵编码中不同语法元素的贡献百分比,并逐个开发语法元素的码率模型以构建整个TU级模型。首先,对系数进行自适应加权,以区分不同系数对码率的不均匀贡献。然后,定义位置参数以描述一个块内非零系数可能的分布模式。通过统计方式对大量样本的模型参数进行微调,得出最终线性码率模型。最后,建立了变换域失真模型来省略不必要的重构过程。实验结果表明,所提算法在RA配置下,可以实现49.76%的复杂度降低,而BD-BR仅增加1.74%。

Statistical modeling based fast rate distortion estimation algorithm for HEVC

To reduce the coding computational complexity of the rate and distortion calculations in HEVC,a fast TU level rate model with higher accuracy was proposed.The contribution percentages of different syntax elements in entropy coding were evaluated,and syntax element-wise accurate rate models were individually developed to construct the whole TU level model.In addition,coefficient levels were weighted adaptively to distinguish the nonuniform contributions of different coefficients in terms of rate profiling.Moreover,position-wise parameter was defined to depict the distribution patterns for possible non-zero coefficients within one block.The final linear rate model was developed by fine-tuning the model parameters from great amounts of samples in a statistical way.Finally,the transform domain distortion model was also established to bypass unnecessary reconstruction process.Experimental results show that the proposed algorithm can achieve 49.76%complexity reduction with 1.74%BD-BR increase for RA configuration.