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Polynomial Spline Signal Processing Algorithms (1992)
| Content Provider | CiteSeerX |
|---|---|
| Author | Unser, Michael Aldroubi, Ateram |
| Description | We describe new digital filtering algorithms for the processing and representation of signals using polynomial splines. We fast consider the classical polynomial spline interpolation problem and show that it can be solved efficiently by recursire digital filtering. This result also yields a simple procedure for signal differentiation. We then derive ters that efficiently solve the problem of smoothing spline approximations. This technique is a regularized version of spline interpolation and is therefore less sensitive to noise It is applied to the design of a robust edge detection algorithm with an adjustable scale parameter. Finally, we describe a filtering/sampling algorithm for least squares spline approximation. This data reduction technique is applied to the generation of a cubic spline image pyramid that is found to compare favorably with the Gauss/Laplace pyramid. Proc. ICASSP III |
| File Format | |
| Language | English |
| Publisher Date | 1992-01-01 |
| Access Restriction | Open |
| Subject Keyword | Recursire Digital Filtering Gauss Laplace Pyramid Data Reduction Technique Spline Approximation New Digital Filtering Algorithm Robust Edge Detection Algorithm Adjustable Scale Parameter Polynomial Spline Signal Processing Algorithm Cubic Spline Image Pyramid Simple Procedure Square Spline Approximation Classical Polynomial Spline Interpolation Problem Signal Differentiation Regularized Version Polynomial Spline Spline Interpolation |
| Content Type | Text |
| Resource Type | Article |
