dwt.3d

idwt.3d

Three-dimensional separable discrete wavelet transform (DWT).

Basic wavelet routines for time series (1D), image (2D) and array
(3D) analysis.  The code provided here is based on wavelet methodology
developed in Percival and Walden (2000); Gencay, Selcuk and Whitcher (2001);
the dual-tree complex wavelet transform (DTCWT) from Kingsbury (1999, 2001) as
implemented by Selesnick; and Hilbert wavelet pairs (Selesnick 2001, 2002).
All figures in chapters 4-7 of GSW (2001) are reproducible using this package
and R code available at the book website(s) below.

Brandon Whitcher

waveslim

Basic Wavelet Routines for One-, Two-, and Three-Dimensional
Signal Processing

dwt.3d function

<dl><dt>x</dt>
<dd>input array</dd>
<dt>wf</dt>
<dd>name of the wavelet filter to use in the decomposition</dd>
<dt>J</dt>
<dd>depth of the decomposition, must be a number less than or equal to
log(minZ,Y,Z,2)</dd>
<dt>boundary</dt>
<dd>only <code>"periodic"</code> is currently implemented</dd>
<dt>y</dt>
<dd>an object of class <code>dwt.3d</code></dd></dl>

Arguments

Author

Three Dimensional Separable Discrete Wavelet Transform — dwt.3d

<dl>

<dt>x</dt>
<dd>input array</dd>


<dt>wf</dt>
<dd>name of the wavelet filter to use in the decomposition</dd>


<dt>J</dt>
<dd>depth of the decomposition, must be a number less than or equal to
log(minZ,Y,Z,2)</dd>


<dt>boundary</dt>
<dd>only <code>"periodic"</code> is currently implemented</dd>


<dt>y</dt>
<dd>an object of class <code>dwt.3d</code></dd>

</dl>

dwt.3d: Three Dimensional Separable Discrete Wavelet Transform

Description

Usage

Arguments

Author