Grain boundary analysis of images

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Prince
Prince 2025-1-28
评论： Kanishk 2025-2-11
I have three TEM images taken at different tilt angles, each showing grain boundaries. However, some grain boundaries are missing in each image. I need a MATLAB code to overlay or merge these three images into a single image where the missing boundaries are filled in, creating a more complete representation of the grain structure.
Attached are the images
  1 个评论
Image Analyst
Image Analyst 2025-1-30
The grain/cell sizes and boundary locations are very different in all three images. I mena, just look at the lower left of the three images. If you merged them, like say by taking the min value of all 3 images, then you might have three grain boundaries instead of just one solid one because their boundaries don't overlap well.

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采纳的回答

Image Analyst
Image Analyst 2025-1-31
Ran in:
You might try taking the darkest pixel in each image to combine them. Try this code:
% Demo by Image Analyst
% Initialization steps:
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
clear; % Erase all existing variables. Or clearvars if you want.
workspace; % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 12;
%--------------------------------------------------------------------------------------------------------
% READ IN FIRST IMAGE
folder = pwd;
baseFileName = "predict_al-324-200C_15min_aligned_fov1_-1_testing_saving_75.png";
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~isfile(fullFileName)
% The file doesn't exist -- didn't find it there in that folder.
% Check the entire search path (other folders) for the file by stripping off the folder.
fullFileNameOnSearchPath = baseFileName; % No path this time.
if ~exist(fullFileNameOnSearchPath, 'file')
% Still didn't find it. Alert user.
errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName);
uiwait(warndlg(errorMessage));
return;
end
end
% Read in image file.
grayImage1 = imread(fullFileName);
% Get size
[rows, columns, numberOfColorChannels] = size(grayImage1);
% Get gray scale version of it.
if numberOfColorChannels == 3
grayImage1 = grayImage1(:, :, 1); % Take red channel.
end
% Display the image.
subplot(2, 2, 1);
imshow(grayImage1);
axis('on', 'image');
impixelinfo;
caption = sprintf('Original image : %s', baseFileName);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
% Maximize window.
g = gcf;
g.WindowState = 'maximized';
g.Name = 'Demo by Image Analyst';
g.NumberTitle = 'off';
drawnow;
%--------------------------------------------------------------------------------------------------------
% READ IN SECOND IMAGE
folder = pwd;
baseFileName = "predict_al-324-200C_15min_aligned_fov1_0_testing_saving_75.png";
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~isfile(fullFileName)
% The file doesn't exist -- didn't find it there in that folder.
% Check the entire search path (other folders) for the file by stripping off the folder.
fullFileNameOnSearchPath = baseFileName; % No path this time.
if ~exist(fullFileNameOnSearchPath, 'file')
% Still didn't find it. Alert user.
errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName);
uiwait(warndlg(errorMessage));
return;
end
end
% Read in image file.
grayImage2 = imread(fullFileName);
% Get size
[rows, columns, numberOfColorChannels] = size(grayImage2);
% Get gray scale version of it.
if numberOfColorChannels == 3
grayImage2 = grayImage2(:, :, 1); % Take red channel.
end
% Display the image.
subplot(2, 2, 2);
imshow(grayImage2);
axis('on', 'image');
impixelinfo;
caption = sprintf('Original image : %s', baseFileName);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
%--------------------------------------------------------------------------------------------------------
% READ IN THIRD IMAGE
folder = pwd;
baseFileName = "predict_al-324-200C_15min_aligned_fov1_+1_testing_saving_75.png";
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~isfile(fullFileName)
% The file doesn't exist -- didn't find it there in that folder.
% Check the entire search path (other folders) for the file by stripping off the folder.
fullFileNameOnSearchPath = baseFileName; % No path this time.
if ~exist(fullFileNameOnSearchPath, 'file')
% Still didn't find it. Alert user.
errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName);
uiwait(warndlg(errorMessage));
return;
end
end
% Read in image file.
grayImage3 = imread(fullFileName);
% Get size
[rows, columns, numberOfColorChannels] = size(grayImage3);
% Get gray scale version of it.
if numberOfColorChannels == 3
grayImage3 = grayImage3(:, :, 1); % Take red channel.
end
% Display the image.
subplot(2, 2, 3);
imshow(grayImage3);
axis('on', 'image');
impixelinfo;
caption = sprintf('Original image : %s', baseFileName);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
%--------------------------------------------------------------------------------------------------------
% COMBINE THE IMAGES BY TAKING THE DARKEST PIXEL IN EACH
image3D = cat(3, grayImage1, grayImage2, grayImage3);
finalImage = min(image3D, [], 3);
% Display the image.
% subplot(2, 2, 4);
figure
imshow(finalImage, []);
axis('on', 'image');
impixelinfo;
caption = sprintf('Final image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
  2 个评论
Prince
Prince 2025-2-10
With regard to the images, can you please produce a single image in which there are black pixels at locations where at least one black pixel exists in one of the images?
Image Analyst
Image Analyst 2025-2-10
@Prince yes, you can threshold it and set the pixel values below the threshold to zero while maintaining the values above the threshold like this
mask = finalImage < someThresholdValue; % This is now a binary image - just black and white.
% Set pixels below the threshold equal to zero in finalImage
% while keeping values above the threshold the same.
finalImage(mask) = 0;
Since final image was built using the darkest pixel from each image, it will do what you asked.

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更多回答（2 个）

Kanishk
Kanishk 2025-1-30
编辑：Kanishk 2025-2-3
Hi @Prince
You can use "imadjust" and "min" function in MATLAB to improve the contrast and merge the images. Here is a simple script using the functions.
% Read the images
img1 = imread('1.png');
img2 = imread('0.png');
img3 = imread('-1.png');
% Convert to grayscale if necessary
if size(img1, 3) == 3
img1 = rgb2gray(img1);
end
if size(img2, 3) == 3
img2 = rgb2gray(img2);
end
if size(img3, 3) == 3
img3 = rgb2gray(img3);
end
imshow(img1)
% Enhance contrast (optional)
img1 = imadjust(img1);
img2 = imadjust(img2);
img3 = imadjust(img3);
imshow(img1)
% Overlay images by taking the maximum pixel intensity
mergedImage = min(img1, min(img2, img3));
% Display the result
imshow(mergedImage);
title('Merged TEM Image with Complete Grain Boundaries');
The code produces the below image.
You can further improve the merged image by aligning the individual images. To connect the gray line in the image, select a threshold with suits your needs and convert everything below that threshold to black(0).
mergedImage((mergedImage <= 200)) = 0;
figure, imshow(mergedImage)
You can also look into edge linking. Here is a link to external documentation for same.
https://www.peterkovesi.com/matlabfns/#edgelink
You can learn more about "imadjust" by using the following command in MATLAB.
web(fullfile(docroot, '/images/ref/imadjust.html'))
Edit: Corrected the typo of using "max" function while calculating the "mergedImage". Also, updated the resulting images.
  5 个评论
显示 3更早的评论
Prince
Prince 2025-2-10
With regard to the images, can you please produce a single image in which there are black pixels at locations where at least one black pixel exists in one of the images?
Kanishk
Kanishk 2025-2-11
The 'min' function here takes the minimum of pixels from the three images which will be the blackest pixel. To improve the blacks of the image you can use a threshold to set pixels below from certain threshold to zero.

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Leepakshi
Leepakshi 2025-1-30
编辑：Leepakshi 2025-1-31
Hey Prince,
You can also perform this task using the “imfuse” command in MATLAB. Note that, you must use “method” as “blend” to overlay all the three images, resulting into a more refined image.
This is how final image will look like:
This is how the code will look like:
>> A= imread("A.png");
>> B=imread('B.png');
>> D = imfuse(A,B,"blend");
>> C = imread('C.png');
>> E = imfuse(D,C,"blend");
>> imshow(E);
Here is a link for documentation of imfuse:
https://in.mathworks.com/help/images/ref/imfuse.html
Hope that added value to your task!
  1 个评论
DGM
DGM 2025-1-30
Imfuse() is used for combination of two images. Sequential use of imfuse() is not appropriate.
For 'blend' mode, the blend weight is always 50%, so sequential use with three images means layer weights are 25%-25%-50% instead of 33%-33%-33%
https://www.mathworks.com/matlabcentral/answers/433228-how-to-overlap-more-than-two-images-into-a-one-image-with-matlab
For 'falsecolor' mode, the results will be differently wrong:
https://www.mathworks.com/matlabcentral/answers/303851-how-to-superimpose-many-images-using-loop
For 'checkerboard' mode, sequential use simply replaces one of the prior images:
https://www.mathworks.com/matlabcentral/answers/1439139-how-do-i-fuse-together-4-images-of-the-same-dimensions-together-in-a-checkerboard-like-fashion

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