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231223s2007 xx ||||| 00| ||eng c |
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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| 100 |
1 |
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|a Condat, Laurent
|e verfasserin
|4 aut
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| 245 |
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|a Quasi-interpolating spline models for hexagonally-sampled data
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|c 2007
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|a Text
|b txt
|2 rdacontent
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|a ohne Hilfsmittel zu benutzen
|b n
|2 rdamedia
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|a Band
|b nc
|2 rdacarrier
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| 500 |
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|a Date Completed 07.06.2007
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|a Date Revised 10.12.2019
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|a published: Print
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|a Citation Status MEDLINE
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|a 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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|a Evaluation Study
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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|a Van De Ville, Dimitri
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 16(2007), 5 vom: 28. Mai, Seite 1195-206
|w (DE-627)NLM09821456X
|x 1941-0042
|7 nnas
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| 773 |
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|g volume:16
|g year:2007
|g number:5
|g day:28
|g month:05
|g pages:1195-206
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|a AR
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|d 16
|j 2007
|e 5
|b 28
|c 05
|h 1195-206
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