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Open Access Green as soon as Postprint is submitted to ZB.
Quasi-interpolating spline models for hexagonally-sampled data.
IEEE Trans. Image Process. 16, 1195-1206 (2007)
The reconstruction of a continuous-domain representation from sampled data is an essential element of many image processing tasks, in particular, image resampling. Until today, most image data have been available on Cartesian lattices, despite the many theoretical advantages of hexagonal sampling. In this paper, we propose new reconstruction methods for hexagonally sampled data that use the intrinsically 2-D nature of the lattice, and that at the same time remain practical and efficient. To that aim, we deploy box-spline and hex-spline models, which are notably well adapted to hexagonal lattices. We also rely on the quasi-interpolation paradigm to design compelling prefilters; that is, the optimal filter for a prescribed design is found using recent results from approximation theory. The feasibility and efficiency of the proposed methods are illustrated and compared for a hexagonal to Cartesian grid conversion problem.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
approximation theory; box-splines; hexagonal lattices; hex-splines; interpolation; linear shift invariant signal spaces; quasi-interpolation
ISSN (print) / ISBN
1057-7149
e-ISSN
1941-0042
Quellenangaben
Volume: 16,
Issue: 5,
Pages: 1195-1206
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Institute of Biomathematics and Biometry (IBB)