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Registration Errors: Are They Always Bad for Super-Resolution?

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2 Author(s)
Costa, G.H. ; Dept. of Mech. Eng., Univ. of Caxias do Sul, Caxias do Sul, Brazil ; Bermudez, J.C.M.

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.

Published in:

Signal Processing, IEEE Transactions on  (Volume:57 ,  Issue: 10 )

Date of Publication:

Oct. 2009

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