Quickest way to join images preserving each colormap in MATLAB

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I am a having problem finding a way to join images preserving each colormap. I basically want to read images from a folder, place them in a rectangular grid (image11, image12; image21, image22) each with its own colormap. I have tried imtile() but I get black boxes at times and also for some reason the colormap is a greyscale instead of colours.
What would be the quickest way to do this? maybe forming a supermatrix containing all pixels of all images and then saving that as an image?
My pseudocode is simple:
for namefiles
im = imread(namefile);
imshow(im); %this works
out=imtile(im,'GridSize', [ypos xpos]); %this shows the pictures in black and white
imshow(out)
end
  2 Comments
carlos g
carlos g on 4 Jul 2022
I am actually not convinced that imtile() is what I want, that's why I didn't provide my code, I have now added it. Yes, all images are the same size. I can provide the position in the "grid" by looping indices. Yes, the colours of imshow(im) are the right ones, the colors in imshow(out) are not (black and white for a reason that I don't know).

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Accepted Answer

DGM
DGM on 4 Jul 2022
Edited: DGM on 4 Jul 2022
Read the images into a cell array in the loop. If the images are indexed color images, then convert them to RGB using ind2rgb() before storing them. Call imtile() or montage() on the cell array outside the loop.
nframes = 4;
C = cell(nframes,1);
for f = 1:nframes
[thisframe map] = imread(sprintf('pepframe%d.png',f));
if ~isempty(map)
thisframe = ind2rgb(thisframe,map);
end
C{f} = thisframe;
end
montage(C)
  5 Comments
DGM
DGM on 8 Jul 2022
Edited: DGM on 8 Jul 2022
Ah. I didn't think about that. By default, ind2rgb() produces an array of class 'double'. You can reduce the memory requirements by a factor of 8 by doing:
C{f,sim_case} = im2uint8(thisframe);
If they still won't fit in memory, then the problem gets more complicated. There may have to be some compromises made. If there are further memory issues, it would be helpful to know how large the images actually are (height, width) and how much memory is available. That way I can at least estimate what might fit. If the images are all the same size, the requirements can be reduced by a factor of about 2.
The memory constraints would also mean that using mimread()/imstacker() from MIMT would be out of the question.

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