Research on HEVC screen content coding and video transmission technology based on machine learning

Abstract

With the complexity of the 5 G network environment and the diversified requirements for video transmission, multimedia content transmission in different channel environments is a direction worth studying in order to achieve good performance of digital media content transmission systems in an open network environment. Based on the code stream structure characteristics of screen content in HEVC, this paper has proposed a joint source channel coding (JSCC) scheme to study the transmission of compressed video in wireless channels. Combined with the clustering algorithm from the field of artificial intelligence in the environment of wireless channel classification problem, the parameters of the wireless channel and the influencing factors can be used to reduce the noise and then use the FCM (Fuzzy C-Means) clustering algorithm to classify the channel environment. According to the channel status, optimize the current remaining resources and implement channel coding through LDPC codes. By analyzing and minimizing the end-to-end distortion model, the adaptive bit rate allocation further guarantees the quality of the reconstructed video.