Wavelet Toolbox |
Two-Dimensional Analysis for De-Noising Using the Graphical Interface
In this section, we explore a strategy for de-noising images based on the two-dimensional stationary wavelet analysis using the graphical interface tools. The basic idea is to average many slightly different discrete wavelet analyses.
The Wavelet Toolbox Main Menu appears
Click the SWT De-noising 2-D menu item.
The discrete stationary wavelet transform de-noising tool for images appears.
When the Load Image dialog box appears, select the MAT-file noiswom.mat
, which should reside in the MATLAB directory toolbox/wavelet/wavedemo
. Click the OK button. The noisy woman image is loaded into the SWT De-noising 2-D tool.
haar
wavelet from the Wavelet menu, select 4 from the Level menu, and then click the Decompose Image button.
The tool displays the histograms of the stationary wavelet detail coefficients of the image on the left of the window. These histograms are organized as follows:
The result seems to be oversmoothed and the selected thresholds too aggressive. Nevertheless, the histogram of the residuals is quite good since it is close to a Gaussian distribution, which is the noise introduced to produce the analyzed image noiswom.mat
from a piece of the original image woman.mat
.
The result is quite satisfactory, although it is possible to improve it slightly.
Select the sym6
wavelet and click the Decompose Image button. Use the Sparsity slider to adjust the threshold value close to 40.44, and then click the De-noise button.
Two-Dimensional Analysis Using the Command Line | Importing and Exporting Information from the Graphical Interface |
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