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Inverse discrete stationary wavelet transform 1-D


X = iswt(SWC,'wname')
X = iswt(SWA,SWD,'wname')
X = iswt(SWA(end,:),SWD,'wname')
X = iswt(SWC,Lo_R,Hi_R)
X = iswt(SWA,SWD,Lo_R,Hi_R)
X = iswt(SWA(end,:),SWD,Lo_R,Hi_R)


iswt performs a multilevel 1-D stationary wavelet reconstruction using either an orthogonal or a biorthogonal wavelet. Specify the wavelet using its name ('wname', see wfilters for more information) or its 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 is the reconstruction low-pass filter.

  • Hi_R is the reconstruction high-pass filter.

Lo_R and Hi_R must be the same length.


collapse all

Demonstrate perfect reconstruction using swt and iswt with a biorthogonal wavelet.

load noisbloc
[Lo_D,Hi_D,Lo_R,Hi_R] = wfilters('bior3.5');
[swa,swd] = swt(noisbloc,3,Lo_D,Hi_D);
recon = iswt(swa,swd,Lo_R,Hi_R);
ans = 1.1386e-13


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.

See Also

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Introduced before R2006a

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