Hex-splines: A novel spline family for hexagonal lattices

被引:56
作者
Van De Ville, D [1 ]
Blu, T
Unser, M
Philips, W
Lemahieu, I
Van de Walle, R
机构
[1] Swiss Fed Inst Technol, BIG, CH-1015 Lausanne, Switzerland
[2] Univ Ghent, TELIN, B-9000 Ghent, Belgium
[3] Univ Ghent, ELIS, B-9000 Ghent, Belgium
关键词
approximation theory; bivariate splines; hexagonal lattices; sampling theory;
D O I
10.1109/TIP.2004.827231
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper proposes a new family of bivariate, nonseparable splines, called hex-splines, especially designed for hexagonal lattices. The starting point of the construction is the indicator function of the Voronoi cell, which is used to define in a natural way the first-order hex-spline. Higher order hex-splines are obtained by successive convolutions. A mathematical analysis of this new bivariate spline family is presented. In particular, we derive a closed form for a hex-spline of arbitrary order. We also discuss important properties, such as their Fourier transform and the fact they form a Riesz basis. We also highlight the approximation order. For conventional rectangular lattices, hex-splines revert to classical separable tensor-product B-splines. Finally, some prototypical applications and experimental results demonstrate the usefulness of hex-splines for handling hexagonally sampled data.
引用
收藏
页码:758 / 772
页数:15
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