% =========================================================================
% Math 336 - Image Processing - Laboratory 6
%
% Warmup Exercise(s): Image Compression
% Test the compression of the function imwrite.
% 
% Blocked (8x8) wavelet transform replacing DCT. 
%
% Marty Kandes
% Computational Science Research Center / Department of Physics
% San Diego State University
% Fall 2008
% -------------------------------------------------------------------------
clear all; close all; clc;                   % Clear Matlab workspace.
F = imread('lena.jpg');                      % Read in the image.
F = im2double(F);                            % Convert image to double.
F = mat2gray(F);                             % Normalize grayscale image.
imwrite(F,'lenaq90.jpg','jpg','Quality',90); % Write image to file with quality = 90%.
imwrite(F,'lenaq75.jpg','jpg','Quality',75); % Write image to file with quality = 75%.
imwrite(F,'lenaq50.jpg','jpg','Quality',50); % Write image to file with quality = 50%.
imwrite(F,'lenaq25.jpg','jpg','Quality',25); % Write image to file with quality = 25%.
INFO = imfinfo('lena.jpg');                  % Get image info for the original image.
INFOQ90 = imfinfo('lenaq90.jpg');            % Get image info for the quality = 90% image.
INFOQ75 = imfinfo('lenaq75.jpg');            % Get image info for the quality = 75% image.
INFOQ50 = imfinfo('lenaq50.jpg');            % Get image info for the quality = 50% image.
INFOQ25 = imfinfo('lenaq25.jpg');            % Get image info for the quality = 25% image.
[M,N] = size(F);                             % Get dimensions of the image.
B = 8;                                       % Set blocksize. B x B.
A = zeros(B,B);                              % Preallocate block of the image.
H = zeros(B,B);                              % Preallocate block of the wavelet transform.
for J = 1:B:N                                %
    for I = 1:B:M                            % 
        A = F(I:1:I+B-1,J:1:J+B-1);          % Get current image block.
        H = haarmtx(B);                      % Build Haar transform matrix.
        A = H*A*H';                          % Apply 2D Haar transform on image block.
        %A = im2bw(A,graythresh(A));          % Binary threshold the image block.
        A = mat2gray(A);                     % Grayscale threshold / rescaling.
        F(I:1:I+B-1,J:1:J+B-1) = A;          % Put transformed block back in image.
    end;                                     %
end;                                         %
imshow(F);                                   %
imwrite(F,'lenahwtqgray.jpg','jpg');           %
for J = 1:B:N                                %
    for I = 1:B:M                            % 
        A = F(I:1:I+B-1,J:1:J+B-1);          % Get current image block.
        H = haarmtx(B);                      % Build Haar transform matrix.
        A = H'*A*H;                          % Apply 2D inverse Haar transform on image block.
        F(I:1:I+B-1,J:1:J+B-1) = A;          % Put transformed block back in image.
    end;                                     %
end;                                         %
figure;                                      %
imshow(F);                                   %
imwrite(F,'lenaihwtqgray.jpg','jpg');          %

        
        
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