Wavelet Toolbox |
Inverse discrete stationary wavelet transform 1-D
Syntax
Description
iswt performs a multilevel 1-D stationary wavelet reconstruction using either a specific orthogonal wavelet ('wname
', see wfilters
for more information) or specific reconstruction filters (Lo_R and Hi_R).
X = iswt(SWC,'wname
') or X = iswt(SWA,SWD,'wname
') or X = iswt(SWA(end,:),SWD,'wname
') reconstructs the signal X based on the multilevel stationary wavelet decomposition structure SWC or [SWA,SWD] (see swt
for more information).
X = iswt(SWC,Lo_R,Hi_R) or X = iswt(SWA,SWD,Lo_R,Hi_R) or X = iswt(SWA(end,:),SWD,Lo_R,Hi_R) reconstruct as above, using filters that you specify.
Lo_R
and Hi_R
must be the same length.
Examples
% Load original 1D signal. load noisbloc; s = noisbloc; % Perform SWT decomposition at level 3 of s using db1. swc = swt(s,3,'db1'); % Second usage. [swa,swd] = swt(s,3,'db1'); % Reconstruct s from the stationary wavelet % decomposition structure swc. a0 = iswt(swc,'db1'); % Second usage. a0bis = iswt(swa,swd,'db1'); % Check for perfect reconstruction. err = norm(s-a0) err = 9.6566e-014 errbis = norm(s-a0bis) errbis = 9.6566e-014
Algorithm
See the section "Stationary Wavelet Transform" in Chapter 6, "Advanced Concepts", of the User's Guide.
References
Nason, G.P.; B.W. Silverman (1995), "The stationary wavelet transform and some statistical applications," Lecture Notes in Statistics, 103, pp. 281-299.
Coifman, R.R.; Donoho D.L. (1995), "Translation invariant de-noising," Lecture Notes in Statistics, 103, pp 125-150.
Pesquet, J.C.; H. Krim, H. Carfatan (1996), "Time-invariant orthonormal wavelet representations," IEEE Trans. Sign. Proc., vol. 44, 8, pp. 1964-1970.
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