Superresolution restoration of an image sequence: Adaptive filtering approach

This paper presents a new method based on adaptive filtering theory for sup erresolution restoration of continuous image sequences, The proposed method ology suggests least squares (LS) estimators which adapt in time, based on adaptive filters, least mean squares (LMS) or recursive least squares (RLS) . The adaptation enables the treatment of linear space and time-variant blu rring and arbitrary motion, both of them assumed known. The proposed new ap proach is shown to be of relatively low computational requirements, Simulat ions demonstrating the superresolution restoration algorithms are presented .