% Define the directory containing your images
imageDir = 'data/result_Zero_DCE++/ExDark_Gladnet';

% List all image files in the directory
imageFiles = dir(fullfile(imageDir, '*.jpg')); % Update extension as needed

% Initialize arrays to store results
imageNames = cell(numel(imageFiles), 1);
niqeScores = zeros(numel(imageFiles), 1);
brisqueScores = zeros(numel(imageFiles), 1);
piqeScores = zeros(numel(imageFiles), 1);
InformationEntropy= zeros(numel(imageFiles), 1);
edgeMeanIntensity= zeros(numel(imageFiles), 1);
edgeStdIntensity= zeros(numel(imageFiles), 1);
edgeDensity= zeros(numel(imageFiles), 1);
cornerDensity= zeros(numel(imageFiles), 1);
contrast= zeros(numel(imageFiles), 1);
correlation= zeros(numel(imageFiles), 1);
energy= zeros(numel(imageFiles), 1);
homogeneity= zeros(numel(imageFiles), 1);
% Loop through each image
for i = 1:numel(imageFiles)
    % Read the image
    imagePath = fullfile(imageDir, imageFiles(i).name);
    img = imread(imagePath);
    
    % Convert image to grayscale if needed
    if size(img, 3) == 3
        img = rgb2gray(img);
    end
    
    % Calculate NIQE score
    niqeScores(i) = niqe(img);
    
    % Calculate BRISQUE score
    brisqueScores(i) = brisque(img);
    
    % Calculate PIQE score
    piqeScores(i) = piqe(img);
    
    % Store the image name
    imageNames{i} = imageFiles(i).name;
    histogram = imhist(img);
    probability = histogram / sum(histogram);
    % Add a small constant to avoid zero probabilities
    epsilon = 1e-10;
    probability = probability + epsilon;
    InformationEntropy(i) = -sum(probability .* log2(probability));

    % Calculate some basic edge features
    edges = edge(img, 'sobel');
    edgeDensity(i) = sum(edges(:)) / numel(edges);
    edgeMeanIntensity(i) = mean(img(edges));
    edgeStdIntensity(i) = std(double(img(edges)));

    % calculate corner density
    corners = detectHarrisFeatures(img);
    cornerDensity(i)= corners.Count/numel(img);
    
    % Create a GLCM matrix
    glcm = o,
    % Calculate texture features from GLCM
    contrast(i) = graycoprops(glcm, 'Contrast').Contrast;
    correlation(i) = graycoprops(glcm, 'Correlation'). Correlation;
    energy(i) = graycoprops(glcm, 'Energy').Energy;
    homogeneity(i) = graycoprops(glcm, 'Homogeneity'). Homogeneity;
end

% Create a table to store results
resultsTable = table(imageNames, niqeScores, brisqueScores, piqeScores, InformationEntropy,edgeDensity, cornerDensity, edgeMeanIntensity, edgeStdIntensity, contrast, correlation, energy, homogeneity, 'VariableNames', {'ImageName', 'NIQEScore', 'BRISQUEScore', 'PIQEScore', 'InformationEntropy','edgeDensity','cornerDensity','edgeMeanIntensity', 'edgeStdIntensity', 'contrast', 'correlation', 'energy', 'homogeneity'});

% Write the table to an Excel file
outputFileName = 'image_quality_scores.xlsx';
writetable(resultsTable, outputFileName);

disp(['Image quality scores saved to ', outputFileName]);