GCOTSC: Green Coding Techniques for Online Teaching Screen Content Implemented in AVS3

Abstract

During and following the global COVID-19 pandemic, the use of screen content coding applications such as large-scale cloud office, online teaching, and teleconferencing has surged. The vast amount of online data generated by these applications, especially online teaching, has become a vital source of Internet video traffic. Consequently, there is an urgent need for low-complexity online teaching screen content (OTSC) coding techniques. Energy-efficient low-complexity green coding techniques for OTSC, named GCOTSC, are proposed based on the unique characteristics of OTSC. In the inter-frame prediction mode, the input frames are first divided into visually constant frames (VCFs) and non-VCFs using a VCF identifier. A new VCF mode has been proposed to code VCFs efficiently. In the intra-frame prediction mode, a heuristic multi-type least probable option skip mode based on static and dynamic historical information is proposed. Compared with the AVS3 screen content coding algorithm, using the typical online teaching screen content and AVS3 SCC common test condition, the experimental results show that the GOTSC achieves an average 59.06% reduction of encoding complexity in low delay configuration, with almost no impact on coding efficiency.