System level design of a spatio-temporal video resampling architecture

To improve video quality in TV display, we propose an architecture including frame rate up-conversion (FRUC), spatial scaling, and adaptively edge sharpening. The technique of motion compensation is applied both to frame interpolation and to edge sharpening in order to improve visual quality. In conventional methods, the bi-directional motion estimation (ME) is usually employed between two successive frames to interpolate a new frame. The proposed method not only considers temporal correlation, but also exploits the spatial correlation to determine the covered and uncovered region. The weighting of edge sharpness is determined by the magnitude of motion vector (MV) and mean absolute difference (MAD) of the current block to improve image quality. We implement and verify our architecture on a virtual platform with system level design flow. Simulation results show that our method has better PSNR and image quality.