Notes on Fourier-Bessel wavelets
cs.LG, cs.CV, cs.NA, math.NA
Submitted: 2026-09-22
Updated: 2026-09-22
Code: https://github.com/Smee18/FourierBesselWavelets
License: http://creativecommons.org/licenses/by/4.0/
The gist: These notes develop the mathematical foundations and construction of a Fourier-Bessel wavelet family inspired by the disk harmonics of Shaqfa et al.[9].
Terminology
Abstract
These notes develop the mathematical foundations and construction of a Fourier-Bessel wavelet family inspired by the disk harmonics of Shaqfa et al.[9]. We begin with the relevant properties of Bessel and modified Bessel functions and introduce the wavelet properties required for the construction. We then derive the Fourier-Bessel disk harmonics as solutions to the Helmholtz equation on the unit disk subject to a Neumann boundary condition. Building on this basis, we construct a wavelet family by applying a Gaussian spatial envelope and introducing a zero-mean correction for the zeroth angular order. We derive the corresponding normalisation constants for L squared-based applications and discuss L 1-based normalisation for frequency-domain peak consistency. Finally, we derive a closed-form Fourier-domain representation of the resulting wavelets. The main motivation is the approximately linear spacing, which converges to π between consecutive radial eigenvalues. Rather than replacing the conventional dyadic organisation of wavelet families, this construction lays out the foundation to explore whether a more uniform radial frequency allocation can be useful for applications in which broad and balanced frequency coverage is desirable.
Sources
- Kymatio: Scattering Transforms in Python
- Invariant Scattering Convolution Networks
- Rigid-Motion Scattering for Texture Classification
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