Regularized multichannel restoration approach for globally optimal high-resolution video sequence
Min-Cheol Hong, Moon Gi Kang, Aggelos K. Katsaggelos · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1997
This paper introduces an iterative regularized approach to obtain a high resolution video sequence. A multiple input smoothing convex functional is defined and used to obtain a globally optimal high resolution video sequence. A mathematical model of multiple inputs is described by using the point spread function between the original and bilinearly interpolated images in the spatial domain, and motion estimation between frames in the temporal domain. Properties of the proposed smoothing convex functional are analyzed. An iterative algorithm is utilized for obtaining a solution. The regularization parameter is updated at each iteration step from the partially restored video sequence. Experimental results demonstrate the capability of the proposed approach.