Joint image registration and super-resolution reconstruction based on regularized total least norm

Authors:
Qing Wang;Xiaoli Song
Affiliations:
School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, P.R. China;School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, P.R. China
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

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Abstract

Accurate registration of the low resolution (LR) images is a critical step in image super resolution reconstruction (SRR). Conventional algorithms always use invariable motion parameters derived from registration algorithms, and carry on SRR without considering the registration errors in the disjointed method. In this paper we propose a new method that performs joint image registration and SRR based on regularized total least norm (RTLN), updating the motion parameters and HR image simultaneously. Not only translation but also rotation motion are considered, which makes the motion model more universal. Experimental results have shown that our approach is more effective and efficient than traditional ones.