wfusimg

This example shows how to fuse two images to create a new image.

Load the mask and bust images.

load mask
x1 = X;
load bust
x2 = X;

Merge the two images from level 5 wavelet decompositions using the db2 wavelet. Perform the fusion by taking the mean for both approximations and details.

wv = 'db2';
lv = 5;
xfusmean = wfusimg(x1,x2,wv,lv,'mean','mean');

Merge the two images again, but this time perform the fusion by taking the maximum of the approximations and the minimum for the details.

xfusmaxmin = wfusimg(x1,x2,wv,lv,'max','min');

Plot the original and fused images.

subplot(2,2,1)
image(x1)
axis square
title('Mask')
subplot(2,2,2)
image(x2)
axis square
title('Bust')
subplot(2,2,3)
image(xfusmean)
axis square 
title('Synthesized Image: mean-mean')
subplot(2,2,4)
image(xfusmaxmin)
axis square
title('Synthesized Image: max-min')
colormap(map)

This example shows how to restore an image from two fuzzy versions of an original image.

Load two fuzzy versions of an original image.

load cathe_1
x1 = X;
load cathe_2
x2 = X;

Merge the two images from level 5 wavelet decompositions using the smy4 wavelet. Perform the fusion by taking the maximum of the absolute value of the coefficients for both approximations and details.

wv = 'sym4';
lv = 5;
xfus = wfusimg(x1,x2,wv,lv,'max','max');

Plot the original and fused images.

subplot(2,2,1)
image(x1)
axis square
title('Catherine 1')
subplot(2,2,2)
image(x2)
axis square
title('Catherine 2')
subplot(2,2,3)
image(xfus)
axis square 
title('Synthesized Image')
colormap(map)

This example shows how to fuse two images using a user-defined fusion method.

Load two images of the same size.

load mask
a = X;
load bust
b = X;

Define the fusion method and call the fusion function helperUserFusion. The source code for helperUserFusion is listed in the appendix.

fus_method = struct('name','userDEF','param','helperUserFusion');

Merge the images twice with the user-defined method. First use wfusmat, which fuses the images themselves and not their wavelet decompositions. Then use wfusimg, which fuses the wavelet decompositions.

c = wfusmat(a,b,fus_method);
d = wfusimg(a,b,'db4',5,fus_method,fus_method);

Plot the original and fused images.

tiledlayout(2,2)
nexttile
image(a)
title('Original Image 1')
axis square
nexttile
image(b)
title('Original Image 2')
axis square
nexttile
image(c)
title('Fused Images')
axis square
nexttile
image(d)
title('Fused Decompositions')
axis square
colormap(pink(220))

Visualize the differences between the merged images.

figure
image(c-d)
axis square
colormap(pink(220))

function c = helperUserFusion(A,B)
% This function is in support of the wavelet fusion examples only.
% It may change or be removed in a future release.

% create an upper triangular logical array the same size as A.
d = logical(triu(ones(size(A))));
% set a threshold
t = 0.3;

c = A;
% set the upper triangular portion of the output to a blend
% of A and B
c(d) = t*A(d)+(1-t)*B(d);
% set the lower triangular portion of the output to a different
% blend of A and B
c(~d) = t*B(~d)+(1-t)*A(~d);
end