Unified multiframe super-resolution of matte, foreground, and background

Reconstruction of a super-resolved image from multiple frames and extraction of matte are two popular topics that have been solved independently. In this paper, we advocate a unified framework that assimilates matting within the super-resolution model. We show that joint estimation is advantageous, as super-resolved edge information helps in obtaining a sharp matte, while the matte in turn aids in resolving fine details. We propose a multiframe approach to increase the spatial resolution of the matte, foreground, and background. This is validated extensively on examples from standard matting datasets.