On the Hilbert transform of wavelets

07/22/2011
by   Kunal Narayan Chaudhury, et al.
0

A wavelet is a localized function having a prescribed number of vanishing moments. In this correspondence, we provide precise arguments as to why the Hilbert transform of a wavelet is again a wavelet. In particular, we provide sharp estimates of the localization, vanishing moments, and smoothness of the transformed wavelet. We work in the general setting of non-compactly supported wavelets. Our main result is that, in the presence of some minimal smoothness and decay, the Hilbert transform of a wavelet is again as smooth and oscillating as the original wavelet, whereas its localization is controlled by the number of vanishing moments of the original wavelet. We motivate our results using concrete examples.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/04/2004

Image compression by rectangular wavelet transform

We study image compression by a separable wavelet basis {ψ(2^k_1x-i)ψ(2^...
research
10/25/2017

New results on approximate Hilbert pairs of wavelet filters with common factors

In this paper, we consider the design of wavelet filters based on the Th...
research
04/15/2022

Wavelet Moments for Cosmological Parameter Estimation

Extracting non-Gaussian information from the non-linear regime of struct...
research
02/20/2022

Tight Wavelet Filter Banks with Prescribed Directions

Constructing tight wavelet filter banks with prescribed directions is ch...
research
02/24/2008

Wavelet and Curvelet Moments for Image Classification: Application to Aggregate Mixture Grading

We show the potential for classifying images of mixtures of aggregate, b...
research
04/04/2021

Wavelet Design with Optimally Localized Ambiguity Function: a Variational Approach

In this paper, we design mother wavelets for the 1D continuous wavelet t...
research
07/23/2021

Wavelet Design in a Learning Framework

Wavelets have proven to be highly successful in several signal and image...

Please sign up or login with your details

Forgot password? Click here to reset