c09fcc computes the three-dimensional multi-level discrete wavelet transform (DWT). The initialization function
c09acc must be called first to set up the DWT options.
c09fcc computes the multi-level DWT of three-dimensional data. For a given wavelet and end extension method,
c09fcc will compute a multi-level transform of a three-dimensional array
, using a specified number,
, of levels. The number of levels specified,
, must be no more than the value
returned in
nwlmax by the initialization function
c09acc for the given problem. The transform is returned as a set of coefficients for the different levels (packed into a single array) and a representation of the multi-level structure.
Wang Y, Che X and Ma S (2012) Nonlinear filtering based on 3D wavelet transform for MRI denoising URASIP Journal on Advances in Signal Processing 2012:40
-
1:
– Integer
Input
-
On entry: the number of rows of each two-dimensional frame.
Constraint:
this must be the same as the value
m passed to the initialization function
c09acc.
-
2:
– Integer
Input
-
On entry: the number of columns of each two-dimensional frame.
Constraint:
this must be the same as the value
n passed to the initialization function
c09acc.
-
3:
– Integer
Input
-
On entry: the number of two-dimensional frames.
Constraint:
this must be the same as the value
fr passed to the initialization function
c09acc.
-
4:
– const double
Input
Note: the dimension,
dim, of the array
a
must be at least
.
On entry: the by by three-dimensional input data , where with stored in .
-
5:
– Integer
Input
On entry: the stride separating row elements of each of the sets of frame coefficients in the three-dimensional data stored in
a.
Constraint:
.
-
6:
– Integer
Input
-
On entry: the stride separating corresponding coefficients of consecutive frames in the three-dimensional data stored in
a.
Constraint:
.
-
7:
– Integer
Input
-
On entry: the dimension of the array
c.
Constraint:
, where
is the total number of wavelet coefficients that correspond to a transform with
nwl levels.
-
8:
– double
Output
-
On exit: the coefficients of the discrete wavelet transform. If you need to access or modify the approximation coefficients or any specific set of detail coefficients then the use of
c09fyc or
c09fzc is recommended. For completeness the following description provides details of precisely how the coefficients are stored in
c but this information should only be required in rare cases.
Let
denote the number of coefficients of each type at level
, for
, such that
. Then, letting
and
, for
, the coefficients are stored in
c as follows:
- , for
- Contains the level approximation coefficients, . Note that for computational efficiency reasons these coefficients are stored as in c.
- , for
- Contains the level detail coefficients. These are:
- LLH coefficients if ;
- LHL coefficients if ;
- LHH coefficients if ;
- HLL coefficients if ;
- HLH coefficients if ;
- HHL coefficients if ;
- HHH coefficients if ,
for . See Section 2.1 in the C09 Chapter Introduction for a description of how these coefficients are produced.
Note that for computational efficiency reasons these coefficients are stored as
in
c.
-
9:
– Integer
Input
-
On entry: the number of levels, , in the multi-level resolution to be performed.
Constraint:
, where
is the value returned in
nwlmax (the maximum number of levels) by the call to the initialization function
c09acc.
-
10:
– Integer
Output
-
On exit: the number of coefficients in the first dimension for each coefficient type at each level.
contains the number of coefficients in the first dimension (for each coefficient type computed) at the ()th level of resolution, for .
-
11:
– Integer
Output
-
On exit: the number of coefficients in the second dimension for each coefficient type at each level.
contains the number of coefficients in the second dimension (for each coefficient type computed) at the ()th level of resolution, for .
-
12:
– Integer
Output
-
On exit: the number of coefficients in the third dimension for each coefficient type at each level.
contains the number of coefficients in the third dimension (for each coefficient type computed) at the ()th level of resolution, for .
-
13:
– Integer
Communication Array
-
On entry: contains details of the discrete wavelet transform and the problem dimension as setup in the call to the initialization function
c09acc.
On exit: contains additional information on the computed transform.
-
14:
– NagError *
Input/Output
-
The NAG error argument (see
Section 7 in the Introduction to the NAG Library CL Interface).
The accuracy of the wavelet transform depends only on the floating-point operations used in the convolution and downsampling and should thus be close to machine precision.
The example program shows how the wavelet coefficients at each level can be extracted from the output array
c. Denoising can be carried out by applying a thresholding operation to the detail coefficients at every level. If
is a detail coefficient then
and
is the transformed noise term. If some threshold parameter
is chosen, a simple hard thresholding rule can be applied as
taking
to be an approximation to the required detail coefficient without noise,
. The resulting coefficients can then be used as input to
c09fdc in order to reconstruct the denoised signal. See
Section 10 in
c09fzc for a simple example of denoising.
See the references given in the introduction to this chapter for a more complete account of wavelet denoising and other applications.
This example computes the three-dimensional multi-level discrete wavelet decomposition for
input data using the biorthogonal wavelet of order
(set
in
c09acc) with periodic end extension, prints a selected set of wavelet coefficients and then reconstructs and verifies that the reconstruction matches the original data.