26-Blend 2 Images Quiz

%blend two images
dolphin = imread('a.png');
bicycle = imread('b.png');
result=0.85*dolphin + 0.15 *bicycle
imshow(result);

function output = blend (a,b, alpha)
% todo your cod here finally assigned output =<something>
endfunction
result= blend(dolphin, bicycle, 0.85)

Solution 

%blend two images
dolphin = imread('a.png');
bicycle = imread('b.png');

function output = blend (a,b, alpha)
output= alpha *a + (1-alpha)*b;
endfunction
result= blend(dolphin, bicycle, 0.85)
imshow(results

27- Common Types of Noise

% add noice to image
noise =randn(size(im)).*sigma;
output = im +noise;

28- Image Difference Demo

dolphin= imread('dolphin.png')
bicycle = imread('bicycle.png')

diff = dolphin - bicycle;
imshow(diff);
abs-diff= abs (dolphin - bicycle);
imshow(abs-diff);

% Better use image package
pkg load image:
abs_diff2=imabsdiff(a,b); order does not matter

30- Generate Gassian Noise

% Generate Gassian Noise
some_number= randn();
disp(some_number);

some_number= randn([1,5]);
disp(some_number);

noise= randn([1,100]);
[n,x]= hist(noise, [3 2 1 0 1 2 3]);
disp([x;n]);
plot(x,b);

noise= randn([1,100]);
[n,x]= hist(noise, linspace(-3,3,7));
disp([x;n]);
plot(x,n);

32- Effect of Sigma on Gaussian Noise

noise= randn(size(im)).*sigma;

34-Apply Gaussian Noise Quiz

%apply Gaussian Noise to an image
noise= randn(size(img)).*2;

34-Apply Gaussian Noise sol

%apply Gaussian Noise to an image
img=imread('a.jpg');
imshow(img);
noise= randn(size(img)).*25;
output = img+ noise;
imshow(output);