Wavelet Toolbox |

Extract 2-D approximation coefficients

**Syntax**

A = appcoef2(C,S,'

',N) A = appcoef2(C,S,'*wname*

') A = appcoef2(C,S,Lo_R,Hi_R) A = appcoef2(C,S,Lo_R,Hi_R,N)*wname*

**Description**

`appcoef2`

is a two-dimensional wavelet analysis function.

`appcoef2`

computes the approximation coefficients of a two-dimensional signal.

`A = appcoef2(C,S,`

'

'*wname*`,N)`

computes the approximation coefficients at level `N`

using the wavelet decomposition structure `[C,S]`

(see `wavedec2`

for more information).

'

' is a string containing the wavelet name. Level *wname*`N`

must be an integer such that `0 `

` N `

` size(S,1)-2`

.

`A = appcoef2(C,S,`

'

'*wname*`)`

extracts the approximation coefficients at the last level: `size(S,1)-2`

.

Instead of giving the wavelet name, you can give the filters.

For` A = appcoef2(C,S,Lo_R,Hi_R)`

or `A = appcoef2(C,S,Lo_R,Hi_R,N)`

, `Lo_R`

is the reconstruction low-pass filter and `Hi_R`

is the reconstruction high-pass filter (see `wfilters`

for more information).

**Examples**

% The current extension mode is zero-padding (see

`dwtmode`

). % Load original image. load woman; % X contains the loaded image. % Perform decomposition at level 2 % of X using db1. [c,s] = wavedec2(X,2,'db1'); sizex = size(X) sizex = 256 256 sizec = size(c) sizec = 1 65536 val_s = s val_s = 64 64 64 64 128 128 256 256 % Extract approximation coefficients % at level 2. ca2 = appcoef2(c,s,'db1',2); sizeca2 = size(ca2) sizeca2 = 64 64 % Compute approximation coefficients % at level 1. ca1 = appcoef2(c,s,'db1',1); sizeca1 = size(ca1) sizeca1 = 128 128

**Algorithm**

The algorithm is built on the same principle as `appcoef`

.

appcoef | bestlevt |