imwr.imwd {wavethresh} | R Documentation |
These functions perform the reconstruction stage of Mallat's pyramid algorithm, i.e. the inverse discrete wavelet transform for images.
## S3 method for class 'imwd': imwr(imwd, bc=imwd$bc, verbose = getOption("verbose"), ...) ## S3 method for class 'imwdc': imwr(imwd, bc=imwd$bc, verbose = getOption("verbose"), ...)
imwd |
object of class imwd or imwdc respectively; typically
returned by imwd and threshold.imwd .
|
bc |
character, specifying the boundary handling. It is best left to be the boundary handling specified by default. |
verbose |
logical; if true then informative messages are printed detailing the computations to be performed. |
... |
further arguments to be passed to or from methods. |
Details of the algorithm are to be found in Mallat (1989). As for "imwd" the algorithm works by applying many 1D reconstruction algorithms to the coefficients. The filters used are those described in Daubechies (1988).
This function is a method for the generic function
imwr()
for class imwd
.
It can be invoked by calling imwr(x)
for an
object x
of the appropriate class, or directly by
calling imwr.imwd(x)
regardless of the
class of the object.
A matrix, of dimension determined by the original data set supplied
to the initial decomposition (more precisely, determined by the nlevels
component of the imwd.object). This matrix is the highest resolution
level of the reconstruction. If a imwd
(decomposition) is followed
immediately by a imwr
(reconstruction) then the returned matrix
will be exactly the same as the original image.
Release 2.2 Copyright Guy Nason 1993
see wd
for a list.
example(imwd) # Look at the error summary( abs(c(imwr(imwdL) - lennon)))#around 1e-9 ## Threshold after decomposing an image -- automagically compresses: (tdi <- threshold(imwdL)) ## Now reconstruct; imwr calling imwr.imwdc directly filled.contour(answer <- imwr(tdi))