Registration errors: are they always bad for super-resolution?

Authors:
Guilherme Holsbach Costa;José Carlos M. Bermudez
Affiliations:
Department of Mechanical Engineering, University of Caxias do Sul, Caxias do Sul, Brazil;Department of Electrical Engineering, Federal University of Santa Catarina, Florianópolis, Brazil
Venue:
IEEE Transactions on Signal Processing
Year:
2009

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Abstract

The super-resolution reconstruction (SRR) of images is an ill posed problem. Traditionally, it is treated as a regularized minimization problem. Moreover, one of the major problems concerning SRR is its dependence on an accurate registration. In this paper, we show that a certain amount of registration error may, in fact, be beneficial for the performance of the least mean square SRR (LMS-SRR) adaptive algorithm. In these cases, the regularization term may be avoided, leading to reduction in computational cost that can be important in real-time SRR applications.