calculate mse in matlab

To calculate the Mean Squared Error (MSE) in MATLAB, you can use the immse function. Here's the syntax:

main.m
mseValue = immse(originalImage, reconstructedImage);
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Where:

• originalImage is the original image data.
• reconstructedImage is the reconstructed image data.

Here's an example:

main.m
% Example data
originalImage = imread('original.png');
reconstructedImage = imread('reconstructed.png');

% Calculate MSE
mseValue = immse(originalImage, reconstructedImage);

% Display the MSE
fprintf('The MSE between the original and reconstructed image is: %.2f\n', mseValue);
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Make sure to replace 'original.png' and 'reconstructed.png' with the actual paths to your image files.

The immse function calculates the MSE between the two images by comparing their pixel values. The lower the MSE value, the closer the reconstructed image is to the original image.