With the advent of High Definition Television, it will become desirable to convert existing video sequence data into higher-resolution formats. This conversion process already occurs within the human visual system to some extent, since the perceived spatial resolution of a sequence appears much higher than the actual spatial resolution of an individual frame. This paper addresses how to utilize both the spatial and temporal information present in a sequence in order to generate high-resolution video. A novel observation model based on motion compensated subsampling is proposed for a video sequence. Since the reconstruction problem is ill-posed, Bayesian restoration with a discontinuity-preserving prior image model is used to extract high-resolution image sequences will be shown, with dramatic improvements provided over various single frame interpolation methods.