Cloud Model-Based Dynamic Texture Synthesis for Video Coding

This paper presents a novel cloud model which is designed for the inter prediction coding using virtual frame technique. The virtual frame obtained by typical dynamic texture synthesis methods can have a better prediction result in some regions of the encoding frame than the common reference frames, because the non-linear motion and global illumination change between frames is taken into account. However, there are still many limiting factors for current dynamic texture models, which make the video scenes in virtual frames can´t better reflect the motion and changing trend of the real scenes. The prediction performance of virtual frame is to some degree reduced or covered up. The proposed method firstly combined the powerful computing capabilities of cloud platform and the extrapolation process of dynamic texture synthesis for video codec. Results show that this method can be used as a significant complement to the current virtual frame technique.