Empirical Wavelet Transforms

This toolbox proposes the original implementation of Empirical Wavelet Transforms

Description

In this toolbox, we implement the Empirical Wavelet Transform for 1D and 2D signals/images. The principle consists in detecting Fourier supports on which Littlewood-Paley like wavelets are build. In 2D, we revisit different well-known transforms: tensor wavelets, Littlewood-Paley wavelets, ridgelets and curvelets.

The toolbox also provides the scripts used to generate the experiments in the papers:

- J.Gilles, "Empirical wavelet transform" to appear in IEEE Trans. Signal Processing, 2013.
Preprint available at ftp://ftp.math.ucla.edu/pub/camreport/cam13-33.pdf
- J.Gilles, G.Tran, S.Osher "2D Empirical transforms. Wavelets, Ridgelets and Curvelets Revisited", submitted in SIAM Journal on Imaging Sciences, 2013.
Preprint available at ftp://ftp.math.ucla.edu/pub/camreport/cam13-35.pdf

See the README file inside the archive for more instructions

• MATLAB release: MATLAB 7.13 (R2011b)

[Jerome Gilles]

For people trying to compile ftc_seg.c under Windows, you should add the following lines in the C file if you get some linking error:

double round(double val)
{
return floor(val + 0.5);
}