Improved definition video frame enhancement

Abstract

The human visual system seems to be capable of temporally integrating information in a video sequence in such a way that the perceived spatial resolution of a sequence appears much higher than the spatial resolution of an individual frame. This paper addresses how to utilize both the spatial and temporal information present in an image sequence to create a high-resolution video still. 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 an edge-preserving prior image model is used to extract a high-resolution video frame from a low-resolution sequence. Estimates computed from an image sequence containing a camera pan show dramatic improvement over bilinear, cubic B-spline, and Bayesian single frame interpolations. Improved definition is also shown for a video sequence containing objects moving with independent trajectories.