filename     : p_Gro00
title        : Wiener Splines
entry        : inproceedings
pages        : 12
year         : 1999
author       : Markus H. Gross and Daniel Kleiner
language     : English
month        : October
address      : Institute of Scientific Computing
keywords     : interpolating B-spline curves, signal processing, fitting method
institution  : ETH Zürich
abstract     :
We describe an alternative way of constructing interpolating B-spline curves,
surfaces or volumes in Fourier space which can be used for visualization.
In our approach the interpolation problem is considered from a signal processing
point of view and is reduced to finding an inverse B-spline filter sequence.
The Fourier approach encompasses some advantageous features, such as successive
approximation, compression, fast convolution and hardware support. In addition,
optimal Wiener filtering can be applied to remove noise and distortions from the
initial data points and to compute a smooth, least-squares fitting 'Wiener spline'.
Unlike traditional fitting methods, the described algorithm is simple and easy to
implement. The performance of the presented method is illustrated by some examples
showing the restoration of surfaces corrupted by various types of distortions.