Abstract
In this paper we study the possibility of removing aliasing in a scene from a single observation by designing an alias-free upsampling scheme. We generate the unknown high frequency components of the given partially aliased (low resolution) image by minimizing the total variation of the interpolant subject to the constraint that part of unaliased spectral components in the low resolution observation are known precisely and under the assumption of sparsity in the data. This provides a mathematical basis for exact reproduction of high frequency components with probability approaching one, from their aliased observation. The primary application of the given approach would be in super-resolution imaging. © Springer-Verlag Berlin Heidelberg 2006.
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CITATION STYLE
Jiji, C. V., Neethu, P., & Chaudhuri, S. (2006). Alias-free interpolation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3954 LNCS, pp. 255–266). Springer Verlag. https://doi.org/10.1007/11744085_20
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