csci5521/assignments/hwk03/Problem2.m

function [] = Problem2()

  % file names
  stadium_fn = "stadium.jpg";
  goldy_fn = "goldy.jpg";

  % load image and preprocess it
  goldy_img = double(imread(goldy_fn))/255;
  stadium_img = double(imread(stadium_fn))/255;
  
  % convert RGB images
  goldy_x = reshape(permute(goldy_img, [2 1 3]), [], 3); % convert img from NxMx3 to N*Mx3
  stadium_x = reshape(permute(stadium_img, [2 1 3]), [], 3);

  % get dimensionality of stadium image
  [height, width, depth] = size(stadium_img);

  % set epochs (number of iterations to run algorithm for)
  epochs = 10;

  %%%%%%%%%%
  % 2(a,b) %
  %%%%%%%%%%
  index = 1;
  figure();
  for k = 4:4:12 
    fprintf("k=%d\n", k);

    % call EM on data
    [h, m, Q] = EMG(stadium_x, k, epochs, false);

    % get compressed version of image
    [~,class_index] = max(h,[],2);
    compress = m(class_index,:);

    % 2(a), plot compressed image
    subplot(3,2,index)
    imagesc(permute(reshape(compress, [width, height, depth]),[2 1 3]))
    index = index + 1;

    % 2(b), plot complete data likelihood curves
    subplot(3,2,index)
    x = 1:size(Q);
    c = repmat([1 0 0; 0 1 0], length(x)/2, 1);
    scatter(x,Q,20,c); 
    index = index + 1;
  end
  shg

  %%%%%%%%
  % 2(c) %
  %%%%%%%%
  % get dimensionality of goldy image, and set k=7
  [height, width, depth] = size(goldy_img);
  k = 7;

  % run EM on goldy image
  [h, m, Q] = EMG(goldy_x, k, epochs, false);

  % plot goldy image using clusters from EM
  [~,class_index] = max(h,[],2);
  compress = m(class_index,:);
  figure();
  subplot(2,1,1)
  imagesc(permute(reshape(compress, [width, height, depth]),[2 1 3]))

  %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
  % TODO: plot goldy image after using clusters from k-means
  %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
  % begin code here

  % end code here 
  shg 
  
  %%%%%%%%
  % 2(e) %
  %%%%%%%%
  % run improved version of EM on goldy image 
  [h, m, Q] = EMG(goldy_x, k, epochs, true);

  % plot goldy image using clusters from improved EM
  [~,class_index] = max(h,[],2);
  compress = m(class_index,:);
  figure();
  imagesc(permute(reshape(compress, [width, height, depth]),[2 1 3]))
  shg
end