c=wpfbt(f,wt); [c,info]=wpfbt(...);
| f | Input data. |
| wt | Wavelet Filterbank tree definition. |
| c | Coefficients stored in a cell-array. |
| info | Transform parameters struct. |
c=wpfbt(f,wt) returns wavelet packet coefficients c obtained by applying a wavelet filterbank tree defined by wt to the input data f.
[c,info]=wpfbt(f,wt) additionally returns struct. info containing transform parameters. It can be conviniently used for the inverse transform iwpfbt e.g. fhat = iwpfbt(c,info). It is also required by the plotwavelets function.
In contrast to wfbt, the cell array c contain every intermediate output of each node in the tree. c{jj} are ordered according to nodes taken in the breadth-first order.
If f is row/column vector, the coefficient vectors c{jj} are columns. If f is a matrix, the transformation is applied to each of column of the matrix.
The following flags control scaling of intermediate outputs and therefore the energy relations between coefficient subbands. An intermediate output is an output of a node which is further used as an input to a descendant node.
- 'intsqrt'
- Each intermediate output is scaled by 1/sqrt(2). If the filterbank in each node is orthonormal, the overall undecimated transform is a tight frame. This is the default.
- 'intnoscale'
- No scaling of intermediate results is used. This is necessaty for the wpbest function to correctly work with the cost measures.
- 'intscale'
- Each intermediate output is scaled by 1/2.
If 'intnoscale' is used, 'intscale' must be used in iwpfbt (and vice versa) in order to obtain a perfect reconstruction.
Please see help for wfbt description of possible formats of wt and of the additional flags defining boundary handling.
A simple example of calling the wpfbt function using the "full decomposition" wavelet tree:
f = gspi;
J = 6;
[c,info] = wpfbt(f,{'sym10',J,'full'});
plotwavelets(c,info,44100,'dynrange',90);