S2LET: A code to perform fast wavelet analysis on the sphere

TL;DR

S2LET is a fast, robust software for wavelet analysis on the sphere, enabling efficient, exact or approximate signal reconstruction with support for multiple programming languages and pixelisation schemes.

Contribution

It provides an efficient implementation of scale-discretised wavelet transform on the sphere, including a multiresolution algorithm and support for HEALPix pixelisation.

Findings

Exact signal reconstruction with sampling theorem

Good numerical accuracy with HEALPix pixelisation

Multiresolution algorithm reduces samples needed

Abstract

We describe S2LET, a fast and robust implementation of the scale-discretised wavelet transform on the sphere. Wavelets are constructed through a tiling of the harmonic line and can be used to probe spatially localised, scale-depended features of signals on the sphere. The scale-discretised wavelet transform was developed previously and reduces to the needlet transform in the axisymmetric case. The reconstruction of a signal from its wavelets coefficients is made exact here through the use of a sampling theorem on the sphere. Moreover, a multiresolution algorithm is presented to capture all information of each wavelet scale in the minimal number of samples on the sphere. In addition S2LET supports the HEALPix pixelisation scheme, in which case the transform is not exact but nevertheless achieves good numerical accuracy. The core routines of S2LET are written in C and have interfaces in Matlab, IDL and Java. Real signals can be written to and read from FITS files and plotted as Mollweide projections. The S2LET code is made publicly available, is extensively documented, and ships with several examples in the four languages supported. At present the code is restricted to axisymmetric wavelets but will be extended to directional, steerable wavelets in a future release.