%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% COMP 435 Image Processing Examples
% Z. Li, created 02/01/2009
% 1. image read and display
% 2. color to gray conversion
% 3. filtering
% 4. smoothing and edge detection
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function []=image_processing_demo()
clear;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% read and display image
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
im = imread('lena.bmp'); 
figure(1); imshow(im); hold on;
[x1, y1]=ginput(1); plot(x1, y1, '+r');
[x2, y2]=ginput(1); plot(x2, y2, '+r');
xOffs=x1; yOffs=y1; w=x2-x1+1; h=y2-y1+1;

%%%%%%%%%%%%%%%%%%%%%%%
% access image data
%%%%%%%%%%%%%%%%%%%%%%%
im2 = double(im(xOffs:xOffs+w-1, yOffs:yOffs+h-1));
figure(2); colormap('gray');
subplot(2,2,1); stem(im2(1,:), '.'); title('row 1');
subplot(2,2,2); stem(im2(:,1), '.'); title('col 1');
subplot(2,2,3); imagesc(im2);
subplot(2,2,4); meshz(im2);


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% point operations- histogram equ
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
h1 = imhist(im);
im3 = histeq(im);
h3=imhist(im3); 

figure(3); 
subplot(2,2,1); imhist(im);
subplot(2,2,2); imshow(im); 
subplot(2,2,3); imhist(im3);
subplot(2,2,4); imshow(im3);
input('\n color conversion...');


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% color conversion
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
im1 = imread('lake-superior.jpg');
im2 = imread('lake-zurich-1.jpg');
subplot(2,2,1); imshow(im1);
subplot(2,2,2); imshow(rgb2gray(im1));
subplot(2,2,3); imshow(im2);
subplot(2,2,2); imshow(rgb2gray(im2));


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% filter operations with fspecial
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
figure;
k1 = fspecial('average', 5);
k2 = fspecial('disk', 5);
k3 = fspecial('log'); 
k4 = fspecial('gaussian', 5, 0.8);
subplot(2,2,1); colormap('gray');  stem3(k1, '.'); 
subplot(2,2,2); colormap('gray');  stem3(k2, '.'); 
subplot(2,2,3); colormap('gray');  stem3(k3, '.'); 
subplot(2,2,4); colormap('gray');  stem3(k4, '.'); 
figure;
subplot(2,2,1); imshow(imfilter(im, k1));
subplot(2,2,2); imshow(imfilter(im, k2));
subplot(2,2,3); imshow(imfilter(im, k3));
subplot(2,2,4); imshow(imfilter(im, k4));


%%%%%%%%%%%%%%%%%%%%%%%
% filter operations - smoothing
%%%%%%%%%%%%%%%%%%%%%%%
% build a Gaussian smooth filter:
gf1 = computeGaussianKernel(2); 
gf2 = computeGaussianKernel(8); 
gf3 = computeGaussianKernel(16); 

im_gf1 = imfilter(im, gf1, 'symmetric', 'conv');
im_gf2 = imfilter(im, gf2, 'symmetric', 'conv');
im_gf3 = imfilter(im, gf3, 'symmetric', 'conv');
figure(4);
subplot(2,2,1), imshow(im); title('original lena');
subplot(2,2,2), imshow(im_gf1); title('blured, gaussian, std 4, ');
subplot(2,2,3), imshow(im_gf2); title('blured, gaussian, std 8, ');
subplot(2,2,4), imshow(im_gf3); title('blured, gaussian, std 16, ');


% laplacian filter - edge detection:
kLap1 = fspecial('laplacian', 0.2);
kLap2 = fspecial('laplacian', 0.5);
kLap3 = fspecial('laplacian', 0.8);
im_lap1 = imfilter(im, kLap1, 'symmetric', 'conv');
im_lap2 = imfilter(im, kLap2, 'symmetric', 'conv');
im_lap3 = imfilter(im, kLap3, 'symmetric', 'conv');

figure(5);
subplot(2,2,1), imshow(im); title('original lena');
subplot(2,2,2), imshow(im_lap1); title('alpha=0.2');
subplot(2,2,3), imshow(im_lap1); title('alpha=0.5');
subplot(2,2,4), imshow(im_lap1); title('alpha=0.8');


% edge detector
h1 = [-1 -1 -1; -1 8 -1; -1 -1 -1];
h2 = [-1 -1 -1; 2 2 2; -1 -1 -1];
h3 = [-1 2 -1; -1 2 -1; -1 2 -1];
h4 = [-1 -1 2; -1 2 -1; 2 -1 -1];
h5= h4';
figure(6);
subplot(2,3,1); imshow(im); title('original lena');
subplot(2,3,2); im1 = imfilter(im, h1); imshow(im1); title('h1');
subplot(2,3,3); im2 = imfilter(im, h2); imshow(im2); title('h2');
subplot(2,3,4); im3 = imfilter(im, h3); imshow(im3); title('h3');
subplot(2,3,5); im4 = imfilter(im, h4); imshow(im4); title('h4');
subplot(2,3,6); im5 = imfilter(im, h5); imshow(im5); title('h5');


%%%%%%%%%%%%%%%%%%%%%%%
% filter operations - smoothing 
% average, median vs gaussian
%%%%%%%%%%%%%%%%%%%%%%%
% median filter 4x4
im2 = imnoise(im,'salt & pepper',0.04);
im3 = medfilt2(im2, [4, 4]);

h6 = ones(4,4)./(4*4); % box filter
im4 = imfilter(im2, h6); 

h7 = fspecial('gaussian');
im5 = imfilter(im2, h7); 

figure; 
subplot(2,2,1); imshow(im2); title('noisy lena');
subplot(2,2,2); imshow(im3); title('median filter');
subplot(2,2,3); imshow(im4); title('average');
subplot(2,2,4); imshow(im5); title('gaussian');

%%%%%%%%%%%%%%%%%%%%%%%
% filter operations - edge detection 
% DoG
%%%%%%%%%%%%%%%%%%%%%%%
% more edge detectors: LoG, DoG
% DoG
figure(8);
sgm = 2; t = [0.2 0.4 0.8 0.95]; 
for k=1:length(t)
    edge_map=edge(im, 'canny', t(k), sgm);
    subplot(2,2,k); imshow(edge_map); 
    str=sprintf('DoG: t=%1.1f', t(k)); title(str);
end

%%%%%%%%%%%%%%%%%%%%%%%
% filter operations - edge detection 
% sobel, laplacian of gaussian, prewitt
%%%%%%%%%%%%%%%%%%%%%%%
figure;
im1 = imread('lena.bmp'); 
im2 = imread('cameraman.tif');
k1 = fspecial('log');
k2 = fspecial('sobel');
k3 = fspecial('prewitt');
subplot(2,3,1); imshow(imfilter(im1, k1)); title('LoG');
subplot(2,3,2); imshow(imfilter(im1, k2));  title('Sobel');
subplot(2,3,3); imshow(imfilter(im1, k3));  title('Prewitt');
subplot(2,3,4); imshow(imfilter(im2, k1));  title('LoG');
subplot(2,3,5); imshow(imfilter(im2, k2));   title('Sobel');
subplot(2,3,6); imshow(imfilter(im2, k3)); title('Prewitt');


return;