f = iufwt(c,info) f = iufwt(c,w,J);
c | Coefficients stored in \(L \times J+1\) matrix. |
info, w | Transform parameters struct/Wavelet filters definition. |
J | Number of filterbank iterations. |
f | Reconstructed data. |
f = iufwt(c,info) reconstructs signal f from the wavelet coefficients c using parameters from info struct. both returned by ufwt function.
f = iufwt(c,w,J) reconstructs signal f from the wavelet coefficients c using the wavelet filterbank consisting of the J levels of the basic synthesis filterbank defined by w using the "a-trous" algorithm. Node that the same flag as in the ufwt function have to be used.
Please see the help on ufwt for a description of the parameters.
As in ufwt, 3 flags defining scaling of filters are recognized:
- 'sqrt'
- Each filter is scaled by 1/sqrt(a), there a is the hop factor associated with it. If the original filterbank is orthonormal, the overall undecimated transform is a tight frame. This is the default.
- 'noscale'
- Uses filters without scaling.
- 'scale'
- Each filter is scaled by 1/a.
If 'noscale' is used, 'scale' must have been used in ufwt (and vice versa) in order to obtain a perfect reconstruction.
A simple example showing perfect reconstruction:
f = gspi; J = 8; c = ufwt(f,'db8',J); fhat = iufwt(c,'db8',J); % The following should give (almost) zero norm(f-fhat)
S. Mallat. A wavelet tour of signal processing. Academic Press, San Diego, CA, 1998.