Biomedical Imaging GroupSTI
English only   BIG > Publications > A Perfect Fit

 Home Page
 News & Events
 Tutorials and Reviews
 Download Algorithms

 All BibTeX References

Splines: A Perfect Fit for Signal Processing

M. Unser

Plenary talk, Tenth European Signal Processing Conference (EUSIPCO'00), Tampere, Finland, September 4-8, 2000.

Splines, which were invented by Schoenberg more than fifty years ago, constitute an elegant framework for dealing with interpolation and discretization problems. They are widely used in computer-aided design and computer graphics, but have been neglected in signal and image processing applications, mostly as a consequence of what I call the "bad press" phenomenon. Thanks to some recent research efforts in signal processing and wavelet-related techniques, the virtues of splines have been revived in our community there is now compelling evidence (several independent studies) that splines offer the best cost-performance tradeoff among available interpolation methods.

In this talk, I will argue that the spline representation is ideally suited for all processing tasks that require a continuous model of signals or images. I will show that most forms of spline fitting (interpolation, least squares approximation, smoothing splines) can be performed most efficiently using recursive digital filters. I will discuss the connection between splines and Shannon's sampling theory. I will also look at their multiresolution properties which make them prime candidates for constructing wavelet bases and computing image pyramids. I will provide multiple illustrations of their use in image processing; these include zooming and visualization, geometric transformation, registration, contour detection, as well as snakes and contour modeling.

AUTHOR="Unser, M.",
TITLE="Splines: {A} Perfect Fit for Signal Processing",
BOOKTITLE="Tenth European Signal Processing Conference
address="Tampere, Finland",
month="September 4-8,",
note="Plenary talk")

© 2000 EURASIP. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from EURASIP.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.