Edge-based combined super-resolution point cloud video streaming

As an important expression of holographic video, point cloud video is widely used in many fields. However, extremely high bandwidth demand and unbearable transmission delay are the biggest obstacles when streaming, and the complexity of its encoding and decoding cannot be ignored. This article addresses the aforementioned difficulties by using super-resolution to reduce the dependence on network bandwidth during video transmission, and incorporates it into third-party platforms to reduce transmission latency. Specifically, we only store video tiles of basic resolution in the server, with the goal of selecting the most suitable resolution for each tile within the perspective within the platform's computing power limitations. We transform it into an optimization problem and solve it through heuristic algorithms. The simulation results show that this scheme is more effective than traditional schemes.