Java Wavelet Demo

Two Scale

Pick

Analysis

Denoise

Compression

Engine

Wavelet-based Multiresolution Analysis

This applet demonstrates the wavelet-based multiresolution analysis. You are encouraged to click in the left figure to choose the subspace. Watch the projection (yellow line) in that subspace shown in the figure at the right side. The original signal is shown in red.

Feel free to choose different signals and wavelets from the menu. Also feel free to switch between the V subspaces (scaling spaces, coarse spaces) and the W subspaces (wavelet spaces, detail spaces). The space spanned by scaling functions give you the averaged information of the signal in the corresponding scale; while the space spanned by wavelets provide detailed information.

It is also enlighting to look the wavelet coefficients, and see the way that the coefficients are organized. You can switch to the wavelet domain by making a choice under the right side figure. Notice that the number of coefficients are halved each time we move to a coarser scale.

You can also save either the original signal or the project to a file on the server. The URL of the file will be returned to you, so you can get the data when needed. If you want to load your own signal, just use the [File/Load...] menu, then enter the URL of the file containing your own data. The format of the file is very simple. Each line in the file should contain the ASCII representation of a number. The demo will only use the first 1024 data points. If the data file contains less than 1024 points, zeros will be padded to your data.

Reference

S. Mallat, A Theory for Multiscale Signal Decomposition: The Wavelet Representation. IEEE Trans. on Pattern and Machine Intelligence. V11 p674-693, 1989.

Copyright Rice University, 1996-1997.

Haitao Guo