how to find principle component analysis of a woven fabric image? i need a code for this

i am working on image processing. in order to compress a have to principle component analysis.can u suggest me some code to find this PCA

Answer 1

[Aditya]

Hi Gnanaprakash,

Performing Principal Component Analysis (PCA) on images for compression involves reducing the dimensionality of the image data while retaining the most significant features. Here's an example code to perform PCA for image compression in MATLAB:

% Load an example image (grayscale)
img = imread('example.jpg'); % Replace with your image file
img = rgb2gray(img); % Convert to grayscale if necessary
img = im2double(img); % Normalize pixel values to [0, 1]

% Flatten the image into a vector
[m, n] = size(img);
img_vector = img(:);

% Center the data by subtracting the mean
img_mean = mean(img_vector);
img_centered = img_vector - img_mean;

% Compute the covariance matrix
covMatrix = cov(img_centered);

% Compute eigenvalues and eigenvectors
[eigenvectors, eigenvaluesMatrix] = eig(covMatrix);
eigenvalues = diag(eigenvaluesMatrix);

% Sort eigenvalues and eigenvectors
[eigenvaluesSorted, idx] = sort(eigenvalues, 'descend');
eigenvectorsSorted = eigenvectors(:, idx);

% Select the top k principal components
k = 50; % Number of principal components to keep
principalComponents = eigenvectorsSorted(:, 1:k);

% Project the data onto the principal components
projectedData = img_centered * principalComponents;

% Reconstruct the image using the top k principal components
reconstructedData = projectedData * principalComponents' + img_mean;

% Reshape the reconstructed data back into an image
compressed_img = reshape(reconstructedData, [m, n]);

% Display the original and compressed images
figure;
subplot(1, 2, 1);
imshow(img);
title('Original Image');

subplot(1, 2, 2);
imshow(compressed_img);
title(['Compressed Image with ', num2str(k), ' Components']);