SUPER - RESOLUTION RECONSTRUCTION OF CONTINUOUS IMAGESEQUENCESMichael

Super-resolution reconstruction algorithms perform a fusion of several low quality images of the same scene into a single improved quality image. As opposed to this STATIC recovery problem, in this paper we deene a DYNAMIC super-resolution task: the restoration of a blurred, decimated, and noisy image sequence. We rst model this problem through state-space equations, showing that this problem can be viewed as a sequence of STATIC super-resolution problems. Two eecient reconstruction algorithms are proposed, both being adap-tive ltering approximations of the Kalman lter; the R-SD and the R-LMS. Computer simulations on synthetic sequences indicate the computational feasibility of these algorithms.