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Discrete stationary 2-D wavelet transform

`[`

returns the approximation coefficients `A`

,`H,V,D`

] = swt2(`X`

,`N`

,`wname`

)`A`

and the horizontal,
vertical, and diagonal detail coefficients `H`

, `V`

,
and `D`

, respectively, of the stationary 2-D wavelet decomposition of
the image `X`

at level `N`

using the wavelet
`wname`

.

**Note**

`swt2`

is uses periodic extension.`swt2`

uses double-precision arithmetic internally and returns double-precision coefficient matrices.`swt2`

warns if there is a loss of precision when converting to double.

returns the
approximation and detail coefficients in `swc`

= swt2(___)`swc`

.

[1] Nason, G. P., and B. W. Silverman.
“The Stationary Wavelet Transform and Some Statistical Applications.” In *Wavelets
and Statistics*, edited by Anestis Antoniadis and Georges Oppenheim, 103:281–99.
New York, NY: Springer New York, 1995.
https://doi.org/10.1007/978-1-4612-2544-7_17.

[2] Coifman, R. R., and D. L. Donoho.
“Translation-Invariant De-Noising.” In *Wavelets and Statistics*, edited
by Anestis Antoniadis and Georges Oppenheim, 103:125–50. New York, NY: Springer New York,
1995. https://doi.org/10.1007/978-1-4612-2544-7_9.

[3] Pesquet, J.-C., H. Krim, and H.
Carfantan. “Time-Invariant Orthonormal Wavelet Representations.” *IEEE Transactions
on Signal Processing* 44, no. 8 (August 1996): 1964–70.
https://doi.org/10.1109/78.533717.