Salvador J, Rivero D, Kochale A, Ruiz-Hidalgo J. Variational Reconstruction and Restoration for Video Super-Resolution. In International Conference on Pattern Recognition (ICPR). Tsukuba, Japan; 2012.  (672.9 KB)


This paper presents a variational framework for obtaining super-resolved video-sequences, based on the observation that reconstruction-based Super-Resolution (SR) algorithms are limited by two factors: registration exactitude and Point Spread Function (PSF) estimation accuracy. To minimize the impact of the first limiting factor, a small-scale linear inpainting algorithm is proposed to provide smooth SR video frames. To improve the second limiting factor, a fast PSF local estimation and total variation-based denoising is proposed. Experimental results reflect the improvements provided by the proposed method when compared to classic SR approaches.