wp.costs.2d(x, cost.fun="entropy", wavelet="s8", n.levels=4, boundary="periodic", precondition=F, dual=F, analysis.filter=NULL, synthesis.filter=NULL, scale=NULL, thresh=NULL, p=2, prob=.5)
"entropy"
,
"threshold"
,
"risk"
,
"sure"
, and "
lp
" are available.
See below for details.
wavelet.packet
for a list of all available wavelet names.
If the length of
wavelet
is one,
the same wavelet is used for both rows and columns.
For user-provided filter, input the values the
filter
argument (see below).
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.
boundary
is one, the same boundary rule is used for both
row and column.
All the boundary rules listed for
dwt
are available except for
"infinite"
and
"polynomial"
.
See
dwt
for the definitions of these rules.
boundary="interval"
only.
See
dwt
for details.
cost.fun
. See below for details.
cost.fun
is
"threshold"
or
"sure"
.
See below for details.
(0,2]
giving the degree of the
lpnorm when
cost.fun
is
"lp"
. See below for details.
(0,1)
, needed when
cost.fun
is
"threshold"
.
See below for details.
pcosts.2d
.
A packet cost object can be used with
the
best.basis
function to select optimal wavelet packet
transforms for images.
Available cost functionals:
entropy
a function of
x
and
scale
.
lp
the usual
Lp
norm,
risk
minimax linear risk.
sure
Stein's Unbiased Risk Estimate.
threshold
number of coefficients above a
threshold
.
phone <- phone-mean(phone) wcost <- wp.costs.2d(phone, wavelet="s8", n.levels=3) bb2 <- best.basis(wcost, data=phone) bb2 plot(bb2)