wave.variance.2d

Produces an estimate of the multiscale variance with approximate 
confidence intervals using the 2D MODWT.

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

wave.variance.2d function

<dl><dt>x</dt>
<dd>image</dd>
<dt>p</dt>
<dd>(one minus the) two-sided p-value for the confidence interval</dd></dl>

Arguments

Author

Wavelet Analysis of Images — wave.variance.2d

<dl>

<dt>x</dt>
<dd>image</dd>


<dt>p</dt>
<dd>(one minus the) two-sided p-value for the confidence interval</dd>

</dl>

wave.variance.2d: Wavelet Analysis of Images

Description

Usage

Value

Arguments

Author

Details

References