cp.costs.2d(x, cost.fun="threshold", n.levels=NULL, taper="poly2",
dct.type=2, boundary="periodic", n.taper=NULL,
scale=NULL, thresh=NULL, p=2, prob=.5)
2^(n.levels[1]) and
column length must be divisible by
2^(n.levels[2]), see below.
Should demean first.
"entropy",
"lp",
"threshold", and
"cpentropy".
See details below.
x is divided into
2^(2*n.levels)
nrow(x)/2^n.levels by
ncol(x)/2^n.levels
blocks. For
"best.basis",
n.levels gives the blocking factor for the finest level.
If
n.levels is bigger than
ml, where
ml is the maximum possible level,
computed from the
max.level function, then
n.levels is set to
ml and
a warning message is given.
2 or
4 indicating, respectively, which of DCT-II or DCT-IV should be used.
See the function
dct for details.
"boxcar", "poly1", "poly2", "poly3", "poly4", "poly5", or
"trig".
See the function
cp.table for details.
"cp.reflect", "periodic"
and
"zero".
See the function
cp.table for details.
2*n.taper.
By default,
n.taper is set to
length(x)/2^(n.level+1),
which is the maximum possible length at the finest blocking level.
"entropy" and
"cpentropy".
The default is
vecnorm(dct.2d(x)). See below for details.
(0,2] giving the degree of the
lp-norm when
cost.fun is
"lp".
See below for details.
cost.fun is
"threshold" or
"sure".
By default,
thresh is the
probth percentile of the
absolute value of the DCT coefficients.
See below for details.
0 and
1 which is used to
compute the threshold
thresh
for when
cost.fun is
"threshold".
See the
thresh argument.
pcosts.2d.
A packet cost object can be used with
the
best.basis function to select optimal cosine packet
transforms for images.
Available cost functionals:
related to
scale.
threshold.
entropy for cosine packets.
The default optional arguments
n.levels, taper, dct.type, boundary
can be reset using function
wavelet.options
,
see
wavelet.options for details.
Wickerhauser, M. V. (1994). Adapted Wavelet Analysis from Theory to Software. A. K. Peters Ltd, Wellesley, MA.
phone <- phone-mean(phone) ccost <- cp.costs.2d(phone, taper="poly2", n.levels=3) bb2 <- best.basis.2d(ccost, phone) bb2 plot(bb2)