Aligning RGB Channels (using SSD) of the given image to produce colored and properly aligned and clear image

Question

The problem statement is -
To search over a window of possible displacements (You will search [-10,10] pixels), score each one using some image matching metric, and take the displacement with the best score. The simplest one is the Sum of Squared Differences (SSD) distance, which simply subtracts one image region from the other and evaluates the sum of the squared values in each pixel. You need to do SSD based calculations on image regions which are of double type.
As R,G,B channels are highly correlated to each other, SSD metric is very likely to work. Your task is to hold the G channel as the reference and move around R and B channels over it and keep track of the SSD value for the 51x51 image regions at the center of the channels. For each channel, you will find the (x,y) displacement vector that gives the minimum SSD value.

The program should divide the image into three equal parts.
The first image is Blue Channel, the second one is Green channel and the last one is Red channel. You have to name your variables as below

Blue channel Image - B
Green channel Image - G
Red channel Image - R

Reference Green Channel center region (51x51) -
ref_img_region (center of this region coincides with the center of image and indexes are always integers) Final aligned image - ColorImg_aligned
Given input image-

Required output image-

I have done this so far and getting the almost same output as required but the compiler is showing incorrect value for ColorImg_aligned.

What's wrong with my code. I am new to Matlab. Sorry if the code is not efficient.

%Read the image
img = imread('course1image.jpg');
[r,c] = size(img);

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

ref_img_region = G;
[rg,cg] = size(ref_img_region);
ref_img_region = ref_img_region(ceil((rg-50)/2) :ceil((rg-50)/2) + 50,ceil((cg-50)/2) :ceil((cg-50)/2) + 50);
%disp(size(ref_img_region));
ref_img_region = double(ref_img_region);

% Naive way
% ColorImg_aligned = cat(3,R,G,B);
% imshow(ColorImg_aligned);

% SSD way
nR = align(G,R);
nB = align(G,B);
ColorImg_aligned = cat(3,nR,G,nB);
imshow(ColorImg_aligned);


function aligned = align(green,red)
    [red_row,red_col] = size(red);
    [green_row,green_col] = size(green);

    % checking SSD for cropped part of the images for faster calculation 
    cropped_red = red(ceil((red_row-50)/2) : ceil((red_row-50)/2) + 50,ceil((red_col-50)/2) :ceil((red_col-50)/2) + 50);
    cropped_green = green(ceil((green_row-50)/2) : ceil((green_row-50)/2) + 50,ceil((green_col-50)/2) :ceil((green_col-50)/2) + 50);

    MiN = 9999999999;
    r_index = 0;
    r_dim = 1;
    for i = -10:10
        for j = 1:2
            ssd =     SSD(cropped_green,circshift(cropped_red,i,j));
            if ssd < MiN
                MiN = ssd;
                r_index = i;
                r_dim = j;
            end
        end
    end
    aligned = circshift(red,r_index,r_dim);
end       

function ssd = SSD(a1,a2)
    x = double(a1)-double(a2);
    ssd = sum(x(:).^2);
end       

Answer 1

Finally I was able to pass the assignment.
I just changed

Y = circshift(A,K,dim)

version of circshift to

Y = circshift(A,[i,j])

I'm still doing the same thing but the compiler accepted the answer this time.
Anybody having thoughts about why this happened?

After modification the code looks like this.

%Read the image
img = imread('course1image.jpg');
[r,c] = size(img);

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

ref_img_region = G;
[rg,cg] = size(ref_img_region);
ref_img_region = ref_img_region(ceil((rg-50)/2) :ceil((rg-50)/2) + 50,ceil((cg-50)/2) :ceil((cg-50)/2) + 50);
%disp(size(ref_img_region));
ref_img_region = double(ref_img_region);

% Naive way
% ColorImg_aligned = cat(3,R,G,B);
% imshow(ColorImg_aligned);

% SSD way
nR = align(G,R);
nB = align(G,B);
ColorImg_aligned = cat(3,nR,G,nB);
imshow(ColorImg_aligned);


function aligned = align(green,red)
    [red_row,red_col] = size(red);
    [green_row,green_col] = size(green);

    % checking SSD for cropped part of the images for faster calculation 
    cropped_red = red(ceil((red_row-50)/2) : ceil((red_row-50)/2) + 50,ceil((red_col-50)/2) :ceil((red_col-50)/2) + 50);
cropped_green = green(ceil((green_row-50)/2) : ceil((green_row-50)/2) + 50,ceil((green_col-50)/2) :ceil((green_col-50)/2) + 50);

    MiN = 9999999999;
    r_index = 0;
    r_dim = 1;
    % Modifications
    for i = -10:10
        for j = -10:10
            ssd =     
SSD(cropped_green,circshift(cropped_red,[i,j])); %circshift(A,[i,j])
            if ssd < MiN
                MiN = ssd;
                r_index = i;
                r_dim = j;
            end
        end
    end
    aligned = circshift(red,[r_index,r_dim]);
end       

function ssd = SSD(a1,a2)
    x = double(a1)-double(a2);
    ssd = sum(x(:).^2);
end 

Output