Reconstruct single branch from 2-D wavelet coefficients
X = wrcoef2('type',C,S,wname,N)
X = wrcoef2('type',C,S,Lo_R,Hi_R,N)
X = wrcoef2('type',C,S,wname)
X
= wrcoef2('type',C,S,Lo_R,Hi_R)
wrcoef2 is a two-dimensional
wavelet analysis function. wrcoef2 reconstructs
the coefficients of an image.
X = wrcoef2(
computes the matrix of reconstructed coefficients of level 'type',C,S,wname,N)N, based on the
wavelet decomposition structure [C,S] (see wavedec2 for more information).
wname is a character vector or string scalar containing the name of the
wavelet (see wfilters for more information). If
'type'
= 'a', approximation coefficients are reconstructed; otherwise if
'type'
= 'h' ('v' or 'd', respectively),
horizontal (vertical or diagonal, respectively) detail coefficients are reconstructed.
Level N must be an integer such that 0 ≤ N ≤ size(S,1)-2 if 'type' =
'a' and such that 1 ≤ N ≤ size(S,1)-2 if 'type' =
'h', 'v', or 'd'.
Instead of giving the wavelet name, you can give the filters.
For X = wrcoef2(, 'type',C,S,Lo_R,Hi_R,N)Lo_R is
the reconstruction low-pass filter and Hi_R is
the reconstruction high-pass filter.
X = wrcoef2(
or 'type',C,S,wname)X
= wrcoef2( reconstruct
coefficients of maximum level 'type',C,S,Lo_R,Hi_R)N = size(S,1)-2.
% The current extension mode is zero-padding (see dwtmode).
% Load an image.
load woman;
% X contains the loaded image.
% Perform decomposition at level 2
% of X using sym5.
[c,s] = wavedec2(X,2,'sym5');
% Reconstruct approximations at
% levels 1 and 2, from the wavelet
% decomposition structure [c,s].
a1 = wrcoef2('a',c,s,'sym5',1);
a2 = wrcoef2('a',c,s,'sym5',2);
% Reconstruct details at level 2,
% from the wavelet decomposition
% structure [c,s].
% 'h' is for horizontal,
% 'v' is for vertical,
% 'd' is for diagonal.
hd2 = wrcoef2('h',c,s,'sym5',2);
vd2 = wrcoef2('v',c,s,'sym5',2);
dd2 = wrcoef2('d',c,s,'sym5',2);
% All these images are of same size sX.
sX = size(X)
sX =
256 256
sa1 = size(a1)
sa1 =
256 256
shd2 = size(hd2)
shd2 =
256 256
If C and S are obtained
from an indexed image analysis (respectively a truecolor image analysis)
then X is an m-by-n matrix
(respectively an m-by-n-by-3
array).
For more information on image formats, see the reference pages
of image and imfinfo functions.