Wavelet Toolbox | ![]() ![]() |
One-Dimensional Analysis for De-noising Using the Graphical Interface
In this section, we explore a strategy to de-noise signals, based on the one-dimensional stationary wavelet analysis using the graphical interface tools. The basic idea is to average many slightly different discrete wavelet analyses.
Starting the Stationary Wavelet Transform De-noising 1-D Tool.
noisbloc.mat
, which should reside in the Matlab directory toolbox/wavelet/wavedemo
.
Performing a Stationary Wavelet Decomposition of the Signal..
db1
wavelet from the Wavelet menu and select 5 from the Level menu, and then click the Decompose Signal button. After a pause for computation, the tool displays the stationary wavelet approximation and detail coefficients of the decomposition. These are also called nondecimated coefficients since they are obtained using the same scheme as for the DWT, but omitting the decimation step (see The Fast Wavelet Transform (FWT) Algorithm).
De-noising a Signal Using the Stationary Wavelet Transform..
Note that the approximation coefficients are not thresholded.
Click the De-noise button.
The result is quite satisfactory, but seems to be oversmoothed around the discontinuities of the signal. This can be seen by looking at the residuals, and zooming on a breakdown point, for example around position 800.
Selecting a Thresholding Method..
The result is of good quality and the residuals look like a white noise sample. To investigate this last point, you can get more information on residuals by clicking the Residuals button.
![]() | One-Dimensional Analysis Using the Command Line | Importing and Exporting Information from the Graphical Interface | ![]() |