clear all;
%clf reset;


% Setup data

image_list = mGetLeftImageFileList;
	   
image_total = size(image_list,1);

%size_list = zeros( 1, image_total );
%MSE_list = zeros( 1, image_total );
%signal_list = zeros( 1, image_total );
%noise_list = zeros( 1, image_total );

%SNR_Results        = ones( image_total+1, 1 )*NaN; 
Rate_Results       = ones( image_total+1, 1 )*NaN;


draw = 0;
Rate_total = 0;

RLE_list = [];

for image_count = 1:image_total
  
  image_name = deblank( image_list( image_count,: ) )
  image = pgmRead( sprintf( '../images/%s', image_name) );
  
  if draw
    figure( 1 );
    mShowImage( image );
  end
  
  image_size = prod( size( image ) );
  size_list( image_count ) = image_size;
  

  M = 8;


  bit_total = 0;
  
  current_level = image;
  Current_Size = size( current_level );
  
  reconstructed_level = zeros( size( image ) );

  while rem( Current_Size, 2 ) == zeros( 1, 2 )
    next_level = mSubsampleAverage( current_level );
    super_next_level = mSupersampleAverage( next_level );
    level_diff = current_level - super_next_level;

    Current_Size
    Level_Rate = mComputeEntropy( level_diff )
    Level_Bits = ceil( Level_Rate*prod( Current_Size ) );
    
    bit_total = bit_total + Level_Bits;

    current_level = next_level;
    Current_Size = size( current_level );

  end
  
  Current_Size
  Level_Rate = mComputeEntropy( current_level )
  Level_Bits = ceil( Level_Rate*prod( Current_Size ) );
  
  bit_total = bit_total + Level_Bits;
  
  Rate = bit_total / prod( size( image ) )
  Rate_total = Rate_total + Rate;
    
  Rate_Results( image_count ) = Rate;
  
  if draw
    figure( 2);
    mShowImage(reconstructed_image);
    drawnow;
  end
  
end


Rate_Results = [ NaN, NaN; [ 1:image_total NaN ]' Rate_Results ]
Average_Rate = Rate_total / image_total