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IEEE Trans Image Process. 2006 Mar;15(3):592-603.

An image super-resolution algorithm for different error levels per frame.

Author information

1
Department of Electrical Engineering, University at Buffalo, The State University of New York, Buffalo, NY 14260, USA. huhe@eng.buffalo.edu

Abstract

In this paper, we propose an image super-resolution (resolution enhancement) algorithm that takes into account inaccurate estimates of the registration parameters and the point spread function. These inaccurate estimates, along with the additive Gaussian noise in the low-resolution (LR) image sequence, result in different noise level for each frame. In the proposed algorithm, the LR frames are adaptively weighted according to their reliability and the regularization parameter is simultaneously estimated. A translational motion model is assumed. The convergence property of the proposed algorithm is analyzed in detail. Our experimental results using both real and synthetic data show the effectiveness of the proposed algorithm.

PMID:
16519346
[Indexed for MEDLINE]
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