Wavelet Toolbox™

Wavelet packet tree construction from coefficients

Syntax

• T = cfs2wpt(WNAME,SIZE_OF_DATA,TN_OF_TREE,ORDER,CFS)
  

Description

CFS2WPT builds a wavelet packet tree (T) and the related analyzed signal or image (X) using the following input information:

WNAME: name of the wavelet used for the analysis

SIZE_OF_DATA: size of the analyzed signal or image

TN_OF_TREE: vector containing the terminal node indices of the tree

ORDER: 2 for a signal or 4 for an image

CFS: coefficients used to reconstruct the original signal or image. CFS is optional. When CFS2WPT is used without the CFS input parameter, the wavelet packet tree structure (T) is generated, but all the tree coefficients are null (including X).

Examples

• % Example 1: Using cfs2wpt with the CFS argument
  
  % Loading an image
  load detail
  
  % Building the wavelet packet tree decomposition
  t = wpdec2(X,2,'sym4');
  
  % Reading the coefficient values from the tree
  cfs = read(t,'allcfs');
  
  % Adding noise to the coefficients
  noisyCfs = cfs + 40*rand(size(cfs));
  
  % Building the wavelet packet tree object and the reconstructed
  % noisy image from the noisyCfs using cfs2wpt
  noisyT = cfs2wpt('sym4',size(X),tnodes(t),4,noisyCfs);
  
  % Plotting the new tree and clicking the node (0) or (0,0)
  plot(noisyT)
  
  
  % Example 2: Using cfs2wpt without the CFS argument
  
  % Building an empty wavelet packet tree object 
  t = cfs2wpt('sym4',[1 1024],[3 9 10 2]',2);
  
  % Getting the terminal node sizes
  sN = read(t,'sizes',[3,9]);
  sN3 = sN(1,:); sN9 = sN(2,:);
  
  % Building coefficient values vectors and writing them in the tree
  cfsN3 = ones(sN3);
  cfsN9 = randn(sN9);
  t = write(t,'cfs',3,cfsN3,'cfs',9,cfsN9);
  
  % Plotting the updated tree and clicking the node (9) or (3,2)
  plot(t)
  
  
  

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