NAG Library Function Document

nag_imldwt_2d (c09edc)

1  Purpose

2  Specification

3  Description

4  References

5  Arguments

1:    $\mathbf{nwlinv}$ – IntegerInput

On entry: the number of levels to be used in the inverse multi-level transform. The number of levels must be less than or equal to $n_{\mathrm{fwd}}$, which has the value of argument nwl as used in the computation of the wavelet coefficients using nag_mldwt_2d (c09ecc). The data will be reconstructed to level $\left(\mathbf{nwl}-\mathbf{nwlinv}\right)$, where level $0$ is the original input dataset provided to nag_mldwt_2d (c09ecc).

Constraint: $1\le \mathbf{nwlinv}\le \mathbf{nwl}$, where nwl is the value used in a preceding call to nag_mldwt_2d (c09ecc).

2:    $\mathbf{lenc}$ – IntegerInput

On entry: the dimension of the array c.

Constraint: $\mathbf{lenc}\ge n_{\mathrm{ct}}$, where $n_{\mathrm{ct}}$ is the total number of coefficients that correspond to a transform with nwlinv levels and is unchanged from the preceding call to nag_mldwt_2d (c09ecc).

3:    $\mathbf{c}\left[\mathbf{lenc}\right]$ – const doubleInput

On entry: the coefficients of a multi-level wavelet transform of the original matrix, $A$, which may have been filtered or otherwise manipulated.

Let $q\left(\mathit{i}\right)$ be the number of coefficients (of each type) at level $\mathit{i}$, for $\mathit{i}=n_{\mathrm{fwd}},n_{\mathrm{fwd}}-1,\dots ,1$. Then, setting $k_1=q\left(n_{\mathrm{fwd}}\right)$ and $k_{j+1}=k_j+q\left(n_{\mathrm{fwd}}-⌈j/3⌉+1\right)$, for $j=1,2,\dots ,3n_{\mathrm{fwd}}$, the coefficients are stored in c as follows:

$\mathbf{c}\left[\mathit{i}-1\right]$, for $\mathit{i}=1,2,\dots ,k_1$

Contains the level $n_{\mathrm{fwd}}$ approximation coefficients, $a_{n_{\mathrm{fwd}}}$.

$\mathbf{c}\left[\mathit{i}-1\right]$, for $\mathit{i}=k_j+1,\dots ,k_{j+1}$

Contains the level $n_{\mathrm{fwd}}-⌈j/3⌉+1$ vertical, horizontal and diagonal coefficients. These are:

• vertical coefficients if $j\mathrm{ mod }3=1$;
• horizontal coefficients if $j\mathrm{ mod }3=2$;
• diagonal coefficients if $j\mathrm{ mod }3=0$,

for $j=1,\dots ,3n_{\mathrm{fwd}}$.

Note that the coefficients in c may be extracted according to level and type into two-dimensional arrays using nag_wav_2d_coeff_ext (c09eyc), and inserted using nag_wav_2d_coeff_ins (c09ezc).

4:    $\mathbf{m}$ – IntegerInput

On entry: the number of elements, $m$, in the first dimension of the reconstructed matrix $B$. For a full reconstruction of nwl levels, where nwl is as supplied to nag_mldwt_2d (c09ecc), this must be the same as argument m used in the call to nag_mldwt_2d (c09ecc). For a partial reconstruction of $\mathbf{nwlinv}<\mathbf{nwl}$ levels, this must be equal to $\mathbf{dwtlvm}\left[\mathbf{nwlinv}\right]$, as returned from nag_mldwt_2d (c09ecc).

5:    $\mathbf{n}$ – IntegerInput

On entry: the number of elements, $n$, in the second dimension of the reconstructed matrix $B$. For a full reconstruction of nwl levels, where nwl is as supplied to nag_mldwt_3d (c09fcc), this must be the same as argument n used in the call to nag_mldwt_2d (c09ecc). For a partial reconstruction of $\mathbf{nwlinv}<\mathbf{nwl}$, this must be equal to $\mathbf{dwtlvn}\left[\mathbf{nwlinv}\right]$, as returned from nag_mldwt_2d (c09ecc).

6:    $\mathbf{b}\left[\mathbf{ldb}\times \mathbf{n}\right]$ – doubleOutput

Note: the $\left(i,j\right)$th element of the matrix $B$ is stored in $\mathbf{b}\left[\left(j-1\right)\times \mathbf{ldb}+i-1\right]$.

On exit: the $m$ by $n$ reconstructed matrix, $B$, based on the input multi-level wavelet transform coefficients and the transform options supplied to the initialization function nag_wfilt_2d (c09abc).

7:    $\mathbf{ldb}$ – IntegerInput

On entry: the stride separating matrix row elements in the array b.

Constraint: $\mathbf{ldb}\ge \mathbf{m}$.

8:    $\mathbf{icomm}\left[180\right]$ – const IntegerCommunication Array

On entry: contains details of the discrete wavelet transform and the problem dimension as setup in the call to the initialization function nag_wfilt_2d (c09abc).

9:    $\mathbf{fail}$ – NagError *Input/Output

The NAG error argument (see Section 3.6 in the Essential Introduction).

6  Error Indicators and Warnings

NE_ALLOC_FAIL

Dynamic memory allocation failed.
See Section 3.2.1.2 in the Essential Introduction for further information.

NE_BAD_PARAM

On entry, argument $〈\mathit{\text{value}}〉$ had an illegal value.

NE_INITIALIZATION

Either the initialization function has not been called first or icomm has been corrupted.

Either the initialization function was called with $\mathbf{wtrans}=\mathrm{Nag\_SingleLevel}$ or icomm has been corrupted.

NE_INT

On entry, $\mathbf{lenc}=〈\mathit{\text{value}}〉$.
Constraint: $\mathbf{lenc}\ge 〈\mathit{\text{value}}〉$, the total number of coefficients generated by the preceding call to nag_mldwt_2d (c09ecc).

On entry, $\mathbf{m}=〈\mathit{\text{value}}〉$.
Constraint: $\mathbf{m}\ge 〈\mathit{\text{value}}〉$, the number of coefficients in the first dimension at the required level of reconstruction.

On entry, $\mathbf{n}=〈\mathit{\text{value}}〉$.
Constraint: $\mathbf{n}\ge 〈\mathit{\text{value}}〉$, the number of coefficients in the second dimension at the required level of reconstruction.

On entry, $\mathbf{nwlinv}=〈\mathit{\text{value}}〉$.
Constraint: $\mathbf{nwlinv}\ge 1$.

NE_INT_2

On entry, $\mathbf{ldb}=〈\mathit{\text{value}}〉$ and $\mathbf{m}=〈\mathit{\text{value}}〉$.
Constraint: $\mathbf{ldb}\ge \mathbf{m}$.

On entry, $\mathbf{nwlinv}=〈\mathit{\text{value}}〉$ and $n_{\mathrm{fwd}}=〈\mathit{\text{value}}〉$.
Constraint: $\mathbf{nwlinv}\le n_{\mathrm{fwd}}$.

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.

An unexpected error has been triggered by this function. Please contact NAG.
See Section 3.6.6 in the Essential Introduction for further information.

NE_NO_LICENCE

Your licence key may have expired or may not have been installed correctly.
See Section 3.6.5 in the Essential Introduction for further information.

7  Accuracy

8  Parallelism and Performance

9  Further Comments

10  Example