Wavelet theory demystified
Journal
IEEE Transactions on Signal Processing
Journal Volume
51
Journal Issue
2
Date Issued
2003-01-01
Author(s)
Unser, Michael
Abstract
In this paper, we revisit wavelet theory starting from the representation of a scaling function as the convolution of a B-spline (the regular part of it) and a distribution (the irregular or residual part). This formulation leads to some new insights on wavelets and makes it possible to rederive the main results of the classical theory-including some new extensions for fractional orders-in a self-contained, accessible fashion. In particular, we prove that the B-spline component is entirely responsible for five key wavelet properties: order of approximation, reproduction of polynomials, vanishing moments, multiscale differentiation property, and smoothness (regularity) of the basis functions. We also investigate the interaction of wavelets with differential operators giving explicit time domain formulas for the fractional derivatives of the basis functions. This allows us to specify a corresponding dual wavelet basis and helps us understand why the wavelet transform provides a stable characterization of the derivatives of a signal. Additional results include a new peeling theory of smoothness, leading to the extended notion of wavelet differentiability in the LP-sense and a sharper theorem stating that smoothness implies order.
Subjects
Approximation order | Besov spaces | Hölder smoothness | Multiscale differentiation | Splines | Vanishing moments | Wavelets
Type
journal article