NAG Library Routine Document
C09CCF
1 Purpose
C09CCF computes the one-dimensional multi-level discrete wavelet transform (DWT). The initialization routine
C09AAF must be called first to set up the DWT options.
2 Specification
| SUBROUTINE C09CCF ( | N, X, LENC, C, NWL, DWTLEV, ICOMM, IFAIL) |
| INTEGER | N, LENC, NWL, DWTLEV(NWL+1), ICOMM(100), IFAIL |
| double precision | X(N), C(LENC) |
3 Description
C09CCF computes the multi-level DWT of one-dimensional data. For a given wavelet and end extension method, C09CCF will compute a multi-level transform of a data array,
xi, for
i=1,2,…,n, using a specified number,
nl, of levels. The number of levels specified,
nl, must be no more than the value returned in
NWL by the initialization routine
C09AAF 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.
The notation used here assigns level 0 to the input dataset, x, with level 1 being the first set of coefficients computed, with the detail coefficients, d1, being stored while the approximation coefficients, a1, are used as the input to a repeat of the wavelet transform. This process is continued until, at level nl, both the detail coefficients, dnl, and the approximation coefficients, anl are retained. The output array, C, stores these sets of coefficients in reverse order, starting with anl followed by dnl,dnl-1,…,d1.
4 References
None.
5 Parameters
- 1: N – INTEGERInput
-
On entry: the number of elements, n, in the data array x.
Constraint:
This must be the same as the value
N passed to the initialization routine
C09AAF.
- 2: X(N) – double precision arrayInput
On entry:
X contains the one-dimensional input dataset
xi, for
i=1,2,…,n.
- 3: LENC – INTEGERInput
-
On entry: the dimension of the array
C as declared in the (sub)program from which C09CCF is called.
C must be large enough to contain the number,
nc, of wavelet coefficients. The maximum value of
nc is returned in
NWC by the call to the initialization routine
C09AAF and corresponds to the DWT being continued for the maximum number of levels possible for the given data set. When the number of levels,
nl, is chosen to be less than the maximum, then
nc is correspondingly smaller and
LENC can be reduced by noting that the number of coefficients at each level is given by
ceilingn/2 for
MODE='P' in
C09AAF and
floorn+nf-1/2 for
MODE='H','W','Z', where
n is the number of the input data at that level and
nf is the filter length
NF provided by the call to
C09AAF. At the final level the storage is doubled to contain the set of approximation coefficients.
Constraint:
LENC≥nc, where
nc is the number of approximation and detail coefficients that correspond to a transform with
NWL levels.
- 4: C(LENC) – double precision arrayOutput
-
On exit: the coefficients of a multi-level wavelet transform of the dataset.
If
nanl and
ndi, for
i=nl,nl-1,…,1, are the numbers of approximation and detail coefficients returned in
DWTLEV where the subscript identifies the level and
nanl is stored in
DWTLEV1, then setting
k1=nanl and
kj+1=nanl+
∑
i=1
j
n
d
nl
-i+1
, for
j=1,2,…,nl, the coefficients are stored in
C as follows:
-
C1:k1
- Contains the level nl approximation coefficients, anl.
-
Ck1+1:k2
- Contains the level nl detail coefficients dnl.
-
Ckj+1:kj+1
- Contains the level nl-j+1 detail coefficients, for j=2,…,nl.
- 5: NWL – INTEGERInput
-
On entry: the number of levels in the multi-level resolution to be performed.
Constraint:
1≤NWL≤nl, where
nl is the value returned in
NWL (the maximum number of levels) by the call to the initialization routine
C09AAF.
- 6: DWTLEV(NWL+1) – INTEGER arrayOutput
-
On exit: the number of transform coefficients at each level. DWTLEV1 and DWTLEV2 contain the number of approximation, nanl, and detail coefficients, ndnl, for the final level of resolution (these are equal); DWTLEVi contains the number of detail coefficients,
n
d
nl
-i+2
, for the (nl-i+2)th level, for i=3,…,NWL+1.
- 7: ICOMM(100) – INTEGER arrayCommunication Array
-
On entry: contains details of the discrete wavelet transform and the problem dimension as setup in the call to the initialization routine
C09AAF.
On exit: contains additional information on the computed transform.
- 8: IFAIL – INTEGERInput/Output
-
On entry:
IFAIL must be set to
0,
-1 or 1. If you are unfamiliar with this parameter you should refer to
Section 3.3 in the Essential Introduction for details.
On exit:
IFAIL=0 unless the routine detects an error (see
Section 6).
For environments where it might be inappropriate to halt program execution when an error is detected, the value
-1 or 1 is recommended. If the output of error messages is undesirable, then the value
1 is recommended. Otherwise, if you are not familiar with this parameter, the recommended value is
0.
When the value -1 or 1 is used it is essential to test the value of IFAIL on exit.
6 Error Indicators and Warnings
If on entry
IFAIL=0 or
-1, explanatory error messages are output on the current error message unit (as defined by
X04AAF).
Errors or warnings detected by the routine:
- IFAIL=1
-
On entry,
N is inconsistent with the value passed to the initialization routine
C09AAF.
- IFAIL=3
-
On entry,
LENC<nc, where
nc is the value returned in
NWC by the call to the initialization routine
C09AAF.
- IFAIL=5
-
| On entry, | NWL<1, |
| or | NWL>nl, where nl is the value returned in NWL by the call to the initialization routine C09AAF. |
- IFAIL=7
-
On entry, the initialization routine
C09AAF has not been called first or it has been called with
WTRANS='S', or the communication array
ICOMM has become corrupted.
7 Accuracy
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.
8 Further Comments
The wavelet coefficients at each level can be extracted from the output array
C using the information contained in
DWTLEV on exit (see the descriptions of
C and
DWTLEV in
Section 5). For example, given an input data set,
x, denoising can be carried out by applying a thresholding operation to the detail coefficients at every level. The elements
Ck1+1:knl+1, as described in
Section 5, contain the detail coefficients,
d^ij, for
i=nl,nl-1,…,1 and
j=1,2,…,ndi, where
d^ij=dij+σεij and
σεij is the transformed noise term. If some threshold parameter
α is chosen, a simple hard thresholding rule can be applied as
taking
d-ij to be an approximation to the required detail coefficient without noise,
dij. The resulting coefficients can then be used as input to
C09CDF in order to reconstruct the denoised signal. Note that the number of levels,
nl, stored in
NWL and the numbers of coefficients contained in
DWTLEV, must remain unchanged.
See the references given in the introduction to this chapter for a more complete account of wavelet denoising and other applications.
9 Example
This example performs a multi-level resolution of a dataset using the Daubechies wavelet (see
WAVNAM='DB4' in
C09AAF) using zero end extensions, the number of levels of resolution, the number of coefficients in each level and the coefficients themselves are reused. The original dataset is then reconstructed using
C09CDF.
9.1 Program Text
Program Text (c09ccfe.f)
9.2 Program Data
Program Data (c09ccfe.d)
9.3 Program Results
Program Results (c09ccfe.r)