Hello Ahmed,
The code provided here generates and plots a noisy step image. Here is a breakdown of the code and the appropriate titles for the horizontal and vertical coordinates:
1. Generating the Step Image: The following code creates a 64x64 matrix "step" where the top half (32 rows) is filled with ones, and the bottom half (32 rows) is filled with zeros. Adding 1 to the entire matrix makes the top half filled with 2s and the bottom half filled with 1s.
step = 1 + [ones([32 64]) ; zeros([32 64])];
2. Adding Noise: This adds Gaussian noise with a standard deviation of 0.1 to the step image. The "randn" function generates normally distributed random numbers. The resulting noisy image is stored in "im".
noise = 0.1 * randn(size(step));
im = (step + noise);
im = double(im);
3. Displaying the Noisy Step Image: This displays the noisy step image using the "imshow" function. The [0, 3] range specifies the display range for the image.
figure(1), clf;
subplot(1,2,1); imshow(im, [0, 3]);
4. Plotting a Column of the Noisy Image: This plots the values of the 32nd column of the noisy image. The "plot" function is used to create the plot.
figure(2); clf;
plot(im(:,32));
When plotting the noisy step image and the column of the noisy image, appropriate titles for the horizontal and vertical coordinates can help in understanding the data. Here's a sample code including the same:
% Generate the step image
step = 1 + [ones([32 64]) ; zeros([32 64])];
% Add Gaussian noise
noise = 0.1 * randn(size(step));
im = (step + noise);
im = double(im);
% Display the noisy step image
figure(1), clf;
subplot(1,2,1);
imshow(im, [0, 3]);
title('Noisy Step Image');
xlabel('Pixel Column');
ylabel('Pixel Row');
% Plot the values of the 32nd column of the noisy image
figure(2); clf;
plot(im(:,32));
title('Intensity Values of the 32nd Column');
xlabel('Pixel Row Index');
ylabel('Intensity Value');
Output for the above code:
Hope this helps!
