% clown_treesBW.m loads and displays two Matlab images.  It shows how to do simple
% modifications such as brightening, reverse video, superimposition,
% flipping, and blurring.  It also makes a graph of the gray-scale intensity
% as a surface and contour graph.

orient tall

load clown                            % read a datafile called clown
C=ind2gray(X,map);                    % the variable there is called X
                                      % convert C to a grayscale image
size(C)

load trees                            
T=ind2gray(X,map);
T=T(1:200,1:320);                     % take out a subimage same size as C

figure(1)

subplot(4,2,1)
imshow(C,64);
title('Clown')

subplot(4,2,2)
imshow(T,64);
title('Trees')

subplot(4,2,3)
imshow(max(max(C))-C,64);
title('1 - Clown');

subplot(4,2,4)
imshow(fliplr(T)+0.4,64)
title('Trees + 0.4, reversed');

subplot(4,2,5)
imshow(C.*C,64);
title('Clown * Clown');

subplot(4,2,6)
imshow((4*C+T)/5,64);
title('0.8*Clown + 0.2*Trees');

subplot(4,2,7)
SC=C(:,[20:320 1:19]);
imshow((4*C+SC)/5,64);
title('0.8*Clown + 0.2*Shifted Clown');

subplot(4,2,8)
h = fspecial('gaussian',[5 5]);       % a Gaussian filter        
BC = filter2(h,C);                    % apply filter to get a blurred clown
BC = filter2(h,BC);                   % filter more
BC = filter2(h,BC);  
BC = filter2(h,BC);  
BC = filter2(h,BC);  
BC = filter2(h,BC);  

fprintf('Contrast in original clown %8.4f\n',computecontrast(C));
fprintf('Contrast in blurred  clown %8.4f\n',computecontrast(BC));

imshow(BC,64)                                
title('Blurred Clown')

figure(2)

MC = fliplr(BC')';

subplot(2,1,1)
mesh(MC)
view(-10,50)
xlabel('Horizontal');
ylabel('Vertical');
zlabel('Intensity');
title('Surface plot of blurred clown');

subplot(2,1,2)
contour(MC,40)
title('Contour plot of blurred clown')