#matlab #imageprocessing #programming #question #intermediate

Write a MATLAB program to perform the following image processing tasks on a grayscale image:

1. Load an image named 'cameraman.tif' from the built-in MATLAB dataset.
2. Convert the image to grayscale if it's not already in that format.
3. Apply Gaussian blur with a 5x5 kernel.
4. Perform edge detection using the Sobel operator.
5. Display the original, blurred, and edge-detected images in a single figure with three subplots.
6. Save the edge-detected image as 'edge_result.png'.

% 1. Load the cameraman image
img = imread('cameraman.tif');

% 2. Convert to grayscale if necessary
if size(img, 3) == 3
    img = rgb2gray(img);
end

% 3. Apply Gaussian blur with 5x5 kernel
blurred = imgaussfilt(img, 2); % sigma=2 for 5x5 kernel

% 4. Perform edge detection using Sobel operator
edges = edge(blurred, 'sobel');

% 5. Display all images in subplots
figure;
subplot(1,3,1);
imshow(img);
title('Original Image');
axis off;

subplot(1,3,2);
imshow(blurred);
title('Gaussian Blurred');
axis off;

subplot(1,3,3);
imshow(edges);
title('Edge Detected (Sobel)');
axis off;

% 6. Save the edge-detected image
imwrite(edges, 'edge_result.png');

disp('Image processing completed. Results saved.')

Note: This code assumes that the 'cameraman.tif' image is available in the MATLAB path (it's a built-in dataset). The program processes the image through blurring and edge detection, displays the results in a single figure, and saves the final edge-detected image.

By: @DataScienceQ 🚀