% Initialize video paths and load the video
videoFile = 'FilePath\Movie.avi';
outputClusterVideo = 'FilePath\Clusters_Detected.avi';
outputLargeParticlesVideo = 'FilePath\LargeParticles_Detected.avi';

videoReader = VideoReader(videoFile);
frameRate = videoReader.FrameRate;

% Create VideoWriter objects to save output videos
clusterVideoWriter = VideoWriter(outputClusterVideo, 'Grayscale AVI');
largeParticleVideoWriter = VideoWriter(outputLargeParticlesVideo, 'Grayscale AVI');
clusterVideoWriter.FrameRate = frameRate;
largeParticleVideoWriter.FrameRate = frameRate;

open(clusterVideoWriter);
open(largeParticleVideoWriter);

% Create invisible figures for visualization (won't pop up)
fig1 = figure('Visible', 'off');  % For clusters
fig2 = figure('Visible', 'off');  % For large particles

% Define structuring elements for smoothing
seSmall = strel('disk', 3);  % Smaller smoothing for small features
seLarge = strel('disk', 10);  % Larger smoothing for larger clusters

% Parameters for frame selection
startFrame =1;  % Example start frame
endFrame =3036;   % Example end frame



% Move to the start frame
videoReader.CurrentTime = (startFrame - 1) / frameRate;
frameCount = startFrame;


% Process each frame in the video
while hasFrame(videoReader) && frameCount <= endFrame
    % Read the current frame
    frame = readFrame(videoReader);
    grayFrame = rgb2gray(frame);  % Convert to grayscale if needed

     % Calculate average intensity of the frame
    avgIntensity = mean(grayFrame(:));
    n22=avgIntensity/255;


    % Stretch intensity of each frame
    minIntensity = double(min(grayFrame(:)));
    maxIntensity = double(max(grayFrame(:)));
    
    % Rescale the intensities to [0, 255]
    grayFrame = uint8(255 * (double(grayFrame) - minIntensity) / (maxIntensity - minIntensity));


    disp(['Processing Frame: ' num2str(videoReader.CurrentTime * frameRate)]);




    %% 1. Detect Clusters Using Lower Variance Threshold

  
    flatgrayFrame = imflatfield(grayFrame, 50);  % Radius of 20 pixels for correction
    smoothgrayFrame = imgaussfilt(flatgrayFrame,1.5);  % Radius of 20 pixels for correction
   
   
    % Thresholding could be applied if needed (e.g., 0.5 as a threshold)
    threshold = 0.36;  % Set threshold for converting back to binary
    ClusterMask=imbinarize(smoothgrayFrame,threshold);
    ClusterMask=imcomplement(ClusterMask);
    ClusterMask = bwareaopen(ClusterMask,2);

    
    ClusterMask = imfill(ClusterMask, "holes");
    ClusterMask = bwareaopen(ClusterMask, 40);


 

    % Display and write the binary frame for clusters
    figure(fig1);
    imshow(ClusterMask);
    drawnow;
    writeVideo(clusterVideoWriter, uint8(ClusterMask) * 255);  % Save binary frame

    %% 2. Detect Large Particles Using Higher Variance Threshold
    varianceThresholdHigh =1400/n22;
    binaryLargeParticles = imbinarize(localVariance, varianceThresholdHigh / max(localVariance(:)));
    filteredLargeParticles = bwareaopen(binaryLargeParticles, 2);
    filteredLargeParticles = imfill(filteredLargeParticles, "holes");
    smoothedLargeParticles = imclose(filteredLargeParticles, seSmall);

    % Convert the averaged image to binary (optional)
    % Thresholding could be applied if needed (e.g., 0.5 as a threshold)
    threshold = 0.7;  % Set threshold for converting back to binary
    LargeParticleMask=imbinarize(grayFrame,threshold);
    LargeParticleMask=imcomplement(LargeParticleMask);
    LargeParticleMask = bwareaopen(LargeParticleMask,2);
    LargeParticleMask=imcomplement(LargeParticleMask);


    % Display and write the binary frame for large particles
    figure(fig2);
    imshow(LargeParticleMask);
    drawnow;
    writeVideo(largeParticleVideoWriter, uint8(LargeParticleMask) * 255);  % Save binary frame

    %   % Move to the next frame
    frameCount = frameCount + 1;

end

% Close video writers and figures
close(clusterVideoWriter);
close(largeParticleVideoWriter);
close(fig1);
close(fig2);

disp('Processing completed. Videos saved successfully.');