Wavelet Toolbox    

Single-level inverse discrete 1-D wavelet transform



The idwt command performs a single-level one-dimensional wavelet reconstruction with respect to either a particular wavelet ('wname', see wfilters for more information) or particular wavelet reconstruction filters (Lo_R and Hi_R) that you specify.

X = idwt(cA,cD,'wname') returns the single-level reconstructed approximation coefficients vector X based on approximation and detail coefficients vectors cA and cD, and using the wavelet 'wname'.

X = idwt(cA,cD,Lo_R,Hi_R) reconstructs as above using filters that you specify.

Lo_R and Hi_R must be the same length.

Let la be the length of cA (which also equals the length of cD) and lf the length of the filters Lo_R and Hi_R; then length(X) = LX where LX = 2*la if the DWT extension mode set to periodization. For the other extension modes LX = 2*la-lf+2.

For more information about the different Discrete Wavelet Transform extension modes, see dwtmode.

X = idwt(cA,cD,'wname',L) or X = idwt(cA,cD,Lo_R,Hi_R,L) returns the length-L central portion of the result obtained using idwt(cA,cD,'wname'). must be less than LX.

X = idwt(...,'mode',MODE) computes the wavelet reconstruction using the specified extension mode MODE.

X = idwt(cA,[],...) returns the single-level reconstructed approximation coefficients vector X based on approximation coefficients vector cA.

X = idwt([],cD,...) returns the single-level reconstructed detail coefficients vector X based on detail coefficients vector cD.

idwt is the inverse function of dwt in the sense that the abstract statement idwt(dwt(X,'wname'),'wname') would give back X.



Starting from the approximation and detail coefficients at level j, cAj and cDj, the inverse discrete wavelet transform reconstructs cAj-1, inverting the decomposition step by inserting zeros and convolving the results with the reconstruction filters.

See Also
dwt, dwtmode, upwlev


Daubechies, I. (1992), Ten lectures on wavelets, CBMS-NSF conference series in applied mathematics. SIAM Ed.

Mallat, S. (1989), "A theory for multiresolution signal decomposition: the wavelet representation," IEEE Pattern Anal. and Machine Intell., vol. 11, no. 7, pp. 674-693.

Meyer, Y. (1990), Ondelettes et opérateurs, Tome 1, Hermann Ed. (English translation: Wavelets and operators, Cambridge Univ. Press. 1993.)

  get idwt2