This article is part of the series Super-Resolution Imaging: Analysis, Algorithms, and Applications.

Open Access Research Article

A Frequency Domain Approach to Registration of Aliased Images with Application to Super-resolution

Patrick Vandewalle1*, Sabine Süsstrunk1 and Martin Vetterli12

  • * Corresponding author: Patrick Vandewalle

Author Affiliations

1 Ecole Polytechnique Fédéral de Lausanne, School of Computer and Communication Sciences, Lausanne 1015, Switzerland

2 Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720-1770, USA

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EURASIP Journal on Advances in Signal Processing 2006, 2006:071459  doi:10.1155/ASP/2006/71459


The electronic version of this article is the complete one and can be found online at: http://asp.eurasipjournals.com/content/2006/1/071459


Received:27 November 2004
Revisions received:4 May 2005
Accepted:18 May 2005
Published:21 February 2006

© 2006 Vandewalle et al.

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Super-resolution algorithms reconstruct a high-resolution image from a set of low-resolution images of a scene. Precise alignment of the input images is an essential part of such algorithms. If the low-resolution images are undersampled and have aliasing artifacts, the performance of standard registration algorithms decreases. We propose a frequency domain technique to precisely register a set of aliased images, based on their low-frequency, aliasing-free part. A high-resolution image is then reconstructed using cubic interpolation. Our algorithm is compared to other algorithms in simulations and practical experiments using real aliased images. Both show very good visual results and prove the attractivity of our approach in the case of aliased input images. A possible application is to digital cameras where a set of rapidly acquired images can be used to recover a higher-resolution final image.

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