c09fac computes the three-dimensional discrete wavelet transform (DWT) at a single level. The initialization function c09acc must be called first to set up the DWT options.

2 Specification

#include <nag.h>

void c09fac (Integer m, Integer n, Integer fr, const double a[], Integer lda, Integer sda, Integer lenc, double c[], Integer icomm[], NagError *fail)

The function may be called by the names: c09fac, nag_wav_dim3_sngl_fwd or nag_dwt_3d.

3 Description

c09fac computes the three-dimensional DWT of some given three-dimensional input data, considered as a number of two-dimensional frames, at a single level. For a chosen wavelet filter pair, the output coefficients are obtained by applying convolution and downsampling by two to the input data,

A

, first over columns, next over rows and finally across frames. The three-dimensional approximation coefficients are produced by the low pass filter over columns, rows and frames. In addition there are

7

sets of three-dimensional detail coefficients, each corresponding to a different order of low pass and high pass filters (see the C09 Chapter Introduction). All coefficients are packed into a single array. To reduce distortion effects at the ends of the data array, several end extension methods are commonly used. Those provided are: periodic or circular convolution end extension, half-point symmetric end extension, whole-point symmetric end extension and zero end extension. The total number,

n_{ct}

, of coefficients computed is returned by the initialization function c09acc.

4 References

Daubechies I (1992) Ten Lectures on Wavelets SIAM, Philadelphia

5 Arguments

1: $m$ – 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: $n$ – 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: $fr$ – 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: $a [\dim]$ – const double Input: Note: the dimension, dim, of the array a must be at least $lda \times sda \times fr$ .

On entry: the $m \times n \times fr$ three-dimensional input data $A$ , where $A_{i j k}$ is stored in $a [(k - 1) \times lda \times sda + (j - 1) \times lda + i - 1]$ .
5: $lda$ – 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: $lda \geq m$ .
6: $sda$ – Integer Input: On entry: the stride separating corresponding coefficients of consecutive frames in the three-dimensional data stored in a.

Constraint: $sda \geq n$ .
7: $lenc$ – Integer Input: On entry: the dimension of the array c.

Constraint: $lenc \geq n_{ct}$ , where $n_{ct}$ is the total number of wavelet coefficients, as returned by c09acc.
8: $c [lenc]$ – 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.
The $8$ sets of coefficients are stored in the following order: approximation coefficients (LLL) first, followed by $7$ sets of detail coefficients: LLH, LHL, LHH, HLL, HLH, HHL, HHH, where L indicates the low pass filter, and H the high pass filter being applied to, respectively, the columns of length m, the rows of length n and then the frames of length fr. Note that for computational efficiency reasons each set of coefficients is stored in the order $n_{cfr} \times n_{cm} \times n_{cn}$ (see output arguments nwcfr, nwct and nwcn in c09acc).
9: $icomm [260]$ – 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.
10: $fail$ – NagError * Input/Output: The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).

6 Error Indicators and Warnings

NE_ALLOC_FAIL: Dynamic memory allocation failed.
See Section 3.1.2 in the Introduction to the NAG Library CL Interface for further information.
NE_BAD_PARAM: On entry, argument $⟨ value ⟩$ had an illegal value.
NE_INITIALIZATION: Either the communication array icomm has been corrupted or there has not been a prior call to the initialization function c09acc.

The initialization function was called with $wtrans = Nag_MultiLevel$ .
NE_INT: On entry, $fr = ⟨ value ⟩$ .
Constraint: $fr = ⟨ value ⟩$ , the value of fr on initialization (see c09acc).

On entry, $m = ⟨ value ⟩$ .
Constraint: $m = ⟨ value ⟩$ , the value of m on initialization (see c09acc).

On entry, $n = ⟨ value ⟩$ .
Constraint: $n = ⟨ value ⟩$ , the value of n on initialization (see c09acc).
NE_INT_2: On entry, $lda = ⟨ value ⟩$ and $m = ⟨ value ⟩$ .
Constraint: $lda \geq m$ .

On entry, $lenc = ⟨ value ⟩$ and $n_{ct} = ⟨ value ⟩$ .
Constraint: $lenc \geq n_{ct}$ , where $n_{ct}$ is the number of DWT coefficients returned by c09acc in argument nwct.

On entry, $sda = ⟨ value ⟩$ and $n = ⟨ value ⟩$ .
Constraint: $sda \geq n$ .
NE_INTERNAL_ERROR: An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact NAG for assistance.
See Section 7.5 in the Introduction to the NAG Library CL Interface for further information.
NE_NO_LICENCE: Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library CL Interface for further information.

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 Parallelism and Performance

Background information to multithreading can be found in the Multithreading documentation.

c09fac is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.

Please consult the X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this function. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

9 Further Comments

None.

10 Example

This example computes the three-dimensional discrete wavelet decomposition for

5 \times 4 \times 3

input data using the Haar wavelet,

wavnam = Nag_Haar

, with half point end extension, prints the wavelet coefficients and then reconstructs the original data using c09fbc. This example also demonstrates in general how to access any set of coefficients following a single level transform.

c09fa: FL CL CPP AD PY MB

NAG CL Interfacec09fac (dim3_​sngl_​fwd)

▸▿ Contents

1 Purpose

2 Specification

3 Description

4 References

5 Arguments

6 Error Indicators and Warnings

7 Accuracy

8 Parallelism and Performance

9 Further Comments

10 Example

10.1 Program Text

10.2 Program Data

10.3 Program Results

NAG CL Interface
c09fac (dim3_sngl_fwd)