matlab MTF

MTF (Modulation Transfer Function) in MATLAB refers to the analysis and visualization of the spatial frequency response of an imaging system. It is commonly used in image processing and optics to evaluate the system's ability to accurately reproduce object details.

To calculate the MTF in MATLAB, you can follow these steps:

1. Load the input image or create a test pattern.
2. Convert the image to grayscale if necessary.
3. Extract a line profile from the image along a specific direction.
4. Calculate the Fourier Transform of the line profile.
5. Compute the magnitude spectrum (abs) and normalize it.
6. Plot the MTF curve by plotting the normalized magnitude spectrum against spatial frequency.

Here's an example code snippet that demonstrates calculating and plotting MTF in MATLAB:

% Load the input image
image = imread('input_image.png');

% Convert to grayscale
image_gray = rgb2gray(image);

% Extract line profile along a specific direction
line_profile = improfile(image_gray, [x1, y1], [x2, y2]);

% Calculate Fourier Transform of the line profile
ft_profile = fftshift(fft(line_profile));

% Compute magnitude spectrum and normalize it
magnitude_spectrum = abs(ft_profile);
normalized_spectrum = magnitude_spectrum / max(magnitude_spectrum);

% Calculate spatial frequencies
num_points = numel(line_profile);
sampling_frequency = 1;
spatial_frequency = (-num_points/2 : num_points/2 - 1) / num_points * sampling_frequency;

% Plot MTF curve
plot(spatial_frequency, normalized_spectrum);
xlabel('Spatial Frequency');
ylabel('Normalized Magnitude Spectrum');
title('Modulation Transfer Function');

Remember to replace `'input_image.png'` with the path to your own input image, and adjust the line profile endpoints `[x1, y1]` and `[x2, y2]` according to your desired direction of analysis.

This code calculates the MTF along a single line profile. To obtain a more comprehensive MTF analysis, you can repeat these steps for multiple line profiles or use different techniques like slanted-edge analysis.