f=iwpfbt(c,info); f=iwpfbt(c,wt,Ls);
| c | Coefficients stored in a cell-array. |
| info, wt | Transform parameters struct/Wavelet Filterbank tree. |
| Ls | Length of the reconstructed signal. |
| f | Reconstructed data. |
f = iwpfbt(c,info) reconstructs signal f from the coefficients c using parameters from info struct. both returned by wfbt function.
f = iwpfbt(c,wt,Ls) reconstructs signal f from the coefficients c using filter bank tree defined by wt. Plese see wfbt function for possible formats of wt. The Ls parameter is mandatory due to the ambiguity of reconstruction lengths introduced by the subsampling operation and by boundary treatment methods.
Please see help for wfbt description of possible formats of wt and of the additional flags.
The following flags control scaling of the intermediate coefficients. The intermediate coefficients are outputs of nodes which ale also inputs to nodes further in the tree.
- '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.
- 'intscale'
- Each intermediate output is scaled by 1/2.
If 'intnoscale' is used, 'intscale' must have been used in wpfbt (and vice versa) in order to obtain a perfect reconstruction.
A simple example showing perfect reconstruction using the "full decomposition" wavelet tree:
f = gspi;
J = 7;
wt = {'db10',J,'full'};
c = wpfbt(f,wt);
fhat = iwpfbt(c,wt,length(f));
% The following should give (almost) zero
norm(f-fhat)