Coursera | Computer Vision Basics

  
    
  
Coursera
Computer Vision Basics

ASSIGNMENT=2
%Wrire code to split the image into three equal parts and store them in B, G, R channels
B = img(1:341,1:400);
G = img(342:682,1:400);
R = img(683:1023,1:400);

%concatenate R,G,B channels and assign the RGB image to ColorImg variable
ColorImg = cat(3, R, G, B);
imshow(ColorImg)

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ASSIGNMENT=3
img = imread('cameraman.tif');
[Gx, Gy] = imgradientxy(img);
[Gmag, Gdir] = imgradient(Gx, Gy);

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ASSIGNMENT=4
%Read the image
img = imread('course1image.jpg');

[h, w] = size(img);
oneThird = floor(h/3);

B = img(1:oneThird, :);
G = img(oneThird+1:(2*oneThird), :);
R = img((2*oneThird+1):(3*oneThird), :);

cent_x = (341/2-25);
cent_y = (400/2-25);
ref_img_region = double(G(cent_x:cent_x + 50, cent_y:cent_y + 50));

red_offset = offset(double(R(cent_x:cent_x + 50, cent_y:cent_y + 50)), ref_img_region);
shifted_red = circshift(R, red_offset);

blue_offset = offset(double(B(cent_x:cent_x + 50, cent_y:cent_y + 50)), ref_img_region);
shifted_blue = circshift(B, blue_offset);

ColorImg_aligned = cat(3, shifted_red, G, shifted_blue);
imshow(ColorImg_aligned);

% Find the minimun offset by ssd
function [output] = offset(img1, img2)
    MIN = inf; 
    for x = -10:10
        for y = -10:10
            temp = circshift(img1, [x, y]);
            ssd = sum((img2 - temp).^2, 'all');
            if ssd < MIN
                MIN = ssd;
                output = [x, y];
            end
        end
    end
end