HEVC inter prediction method and its hardware research based on neural network
Compared with H.264,the High Efficiency Video Coding Standard(HEVC)proposes many new technolo-gies,which improve the coding performance,but also significantly increase coding complexity.From the perspective of hardware implementation,this paper optimizes the structure of the existing inter frame CU partition prediction neural network in many aspects,reducing its parameters by 70％,and reducing addition operations and multiplication opera-tions by 60％and 58.2％,respectively.The optimized convolutional neural network parameters are processed by a 10-bit fixed-point number scheme for fixed-point processing,which further effectively reduces the expenditure of hardware resources.Compared with the HEVC reference software(HM16.5),the average loss of BD-BR and BD-PSNR caused by the optimized network is 1.718％and-0.056dB,and the average coding complexity is saved by 35％～52％,and the performance loss caused by fixed-point processing is negligible.
万方数据
维普
