For loop each RGB image channel

I want to make this manual saperated RGB channel code into for loop, each channel will undergo the same calculation. Can anybody help me how to convert it into for loop code?

here the image:

t = imread ('luekemia.png')

%% black & white
bw = imbinarize (t,0.4);
bw = ~bw;
    
%% remove noise
bw2 = bwareaopen (bw,100);

%%separate 3 layer RGB
R = t(:,:,1);
G = t(:,:,2);
B = t(:,:,3);
R(bw2(:)==0) = 255;
G(bw2(:)==0) = 255;
B(bw2(:)==0) = 255;
c = cat(3,R,G,B);

%calculate range R

rmax = max(R(bw2(:)~=0))
rmin = min(R(bw2(:)~=0))

gmax = max(G(bw2(:)~=0))
gmin = min(G(bw2(:)~=0))

bmax = max(B(bw2(:)~=0))
bmin = min(B(bw2(:)~=0))

Answer 1

[DGM]

There are probably more succinct ways, but this is one way. Instead of creating a pile of variables, just put things in an array

t = imread ('https://www.mathworks.com/matlabcentral/answers/uploaded_files/793524/image.jpeg');

bw2 = rgb2gray(t) > 50; % idk what your mask is

c = t;
c(repmat(~bw2,[1 1 3])) = 255;

% calculate min and max for R,G,B masked regions
for cc = 1:3
    thischan = t(:,:,cc);
    maskedrange(1,cc) = min(thischan(bw2));
    maskedrange(2,cc) = max(thischan(bw2));
end
maskedrange 

maskedrange = 2×3

93 67 131 255 251 255

[nurul atikah mohd sharif]

Thank you so much! It work for me. May God bless you for helping me.

[nurul atikah mohd sharif]

i have another question, i have apply you code and make some adjustment.

i have run this code, but it give me error 'Index in position 3 exceeds array bounds (must not exceed 1).'

i share here the segmented images at attachment.

segmented_images2 = cell(1,6);

for j = 1:6 
    segmented_image2 {j} = sprintf('segmented_images2%d.jpg',j);
%     
    
    bw = imbinarize (j,0.4);
    bw =~bw;
    bw2 =bwareaopen (bw,100);

%     bw2 = rgb2gray(j) > 100; % idk what your mask is
    c = j;
    c(repmat(~bw2,[1 1 3])) = 255;
    
    % calculate min and max for R,G,B masked regions
    for cc = 1:3
        thischan = j(:,:,cc);
        
        %calculate range R
        Cmin = min(thischan(bw2));
        Cmax = max(thischan(bw2));
 
        % degree of alpha, beta, gamma
        alpha_degree= dg; %input('Enter alpha in degrees: ');
        beta_degree= dg; %input('Enter beta in degrees: ');
        gamma_degree= dg;  %input('Enter gamma in degrees: ');
        
        alpha=(alpha_degree*pi)/180;
        beta=(beta_degree*pi)/180;
        gamma=(gamma_degree*pi)/180; 
        
        % range definitions
        x_r1 = 0:Cmin;
        x_r2 = Cmin:Cmax;
        x_r3 = Cmax:255;   

        % line gradients
        a1 = tan(alpha);
        a2 = tan(beta);
        a3 = tan(gamma);

        % contrast stretching in regions
        im1 = floor(a1*cc);
        im2 = floor(a1*Cmin + (a2*minus(cc,Cmin)));
        im3 = floor(a2*Cmax+minus(a1,a2)*Cmin + (a3*minus(cc,Cmax)));
       
    end 
    % concatance of output image
    CSsegment_image{j} = cast(im1+im2+im3,'uint8'); %#ok<SAGROW>
    CSsegment_image2{j}(bw2(:)~=0) = Ro(bw2(:)~=0); %#ok<*SAGROW>
    
    subplot(2,2,j);
    imshow(CSsegment_image2{j});
end

[DGM]

There were a number of issues. Here's a first pass. You'll have to fill in where there's missing variables

dg = 10; % dg not defined
segmented_images2 = cell(1,5);

for j = 1:5 % only provided 5 images instead of 6?
    segmented_images2{j} = imread(sprintf('segmented%d.png',j)); % file/variable names differ, need to use imread
    %     
    
    bw = imbinarize (segmented_images2{j},0.4); % need to use an image instead of the index
    bw =~bw;
    bw2 =bwareaopen (bw,100);
    %c = j;
    %c(repmat(~bw2,[1 1 3])) = 255;
    
    % calculate min and max for R,G,B masked regions
    for cc = 1:3
        thischan = segmented_images2{j}(:,:,cc); % need to use an image instead of the index
        
        %calculate range R
        Cmin = min(thischan(bw2(:,:,cc))); % imbinarize generates mask with 3 chans instead of 1
        Cmax = max(thischan(bw2(:,:,cc)));
        
        % degree of alpha, beta, gamma
        alpha_degree= dg; %input('Enter alpha in degrees: ');
        beta_degree= dg; %input('Enter beta in degrees: ');
        gamma_degree= dg;  %input('Enter gamma in degrees: ');
        
        alpha=(alpha_degree*pi)/180;
        beta=(beta_degree*pi)/180;
        gamma=(gamma_degree*pi)/180; 
        
        % range definitions
        x_r1 = 0:Cmin;
        x_r2 = Cmin:Cmax;
        x_r3 = Cmax:255;   
        % line gradients
        a1 = tan(alpha);
        a2 = tan(beta);
        a3 = tan(gamma);
        % contrast stretching in regions
        im1 = floor(a1*cc);
        im2 = floor(a1*Cmin + (a2*minus(cc,Cmin)));
        im3 = floor(a2*Cmax+minus(a1,a2)*Cmin + (a3*minus(cc,Cmax)));
        
    end 
    % concatance of output image
    CSsegment_image2{j} = cast(im1+im2+im3,'uint8'); %#ok<SAGROW> % variable name
    CSsegment_image2{j}(bw2(:)~=0) = Ro(bw2(:)~=0); %#ok<*SAGROW> % Ro is undefined
    
    subplot(2,2,j);
    imshow(CSsegment_image2{j});
end

Answer 2

[Image Analyst]

Not sure what analysis you want to do (you didn't say what the "calculations" were) but I just thought I'd point you to a similar example by the Mathworks:

https://www.mathworks.com/help/images/color-based-segmentation-using-k-means-clustering.html