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