C.B. Newland, D.A. Gray, and D. Gibbins (Australia)
super-resolution, Kalman filter, image reconstruction, con vergence
Video super-resolution is the process of estimating a high resolution image from a motion sequence of low-resolution image frames. This paper examines the convergence prop erties of the modified Kalman filter super-resolution algo rithm introduced in [1]. Most significantly, the ratio of the system and measurement noise variances is shown to be a highly useful control parameter of the convergence rate, super-resolution image sharpness, and the algorithm's be haviour in the presence of noise.
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