Title :
The design of maximally smooth wavelets
Author :
Lang, Michael ; Heller, Peter N.
Author_Institution :
MeVis, Bremen, Germany
Abstract :
A method for designing more regular (more differentiable) scaling functions than the Daubechies (1992) wavelets is presented. The approach is to numerically minimize the Holder exponent (a measure of smoothness) subject to constraints on the autocorrelation sequence of the scaling filter. The “maximally smooth” wavelets which result have a Holder exponent which grows faster than that of the Daubechies orthogonal wavelets, as the filter length increases. This is achieved by relaxing some of the vanishing moment conditions
Keywords :
correlation methods; sequences; smoothing methods; wavelet transforms; Daubechies orthogonal wavelets; Holder exponent; autocorrelation sequence; differentiable scaling functions; filter length; maximally smooth wavelets design; regular scaling functions; scaling filter; vanishing moment conditions; Autocorrelation; Design methodology; Discrete wavelet transforms; Filter bank; Frequency domain analysis; Frequency response; Lungs; Multiresolution analysis; Noise reduction; Signal resolution;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
0-7803-3192-3
DOI :
10.1109/ICASSP.1996.543938
