Modified Kalman filtering for image super-resolution: experimental convergence results

Authors:
Cloudia B. Newland;Douglas A. Gray;Danny Gibbins
Affiliations:
University of Adelaide, Adelaide, South Australia, Australia;University of Adelaide, Adelaide, South Australia, Australia;University of Adelaide, Adelaide, South Australia, Australia
Venue:
SIP '07 Proceedings of the Ninth IASTED International Conference on Signal and Image Processing
Year:
2007

Citing 3
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Abstract

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 properties of the modified Kalman filter super-resolution algorithm 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 behaviour in the presence of noise.