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خطا در کد مطلبزمان کنونی: ۱۳۹۵/۰۹/۱۸، ۰۴:۲۵ ب.ظ
کاربران در حال بازدید این موضوع: 1 مهمان
نویسنده: shima.a
آخرین ارسال: shima.a
پاسخ 1
بازدید 2018

رتبه موضوع:
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خطا در کد مطلب

خطا در کد مطلب

#1
Sad 
سلام . من این 2 تا کد مطلب را که مربوط به فشرده سازی تصویر به روش dct و jpeg هستند را اجرا می کنم ولی error می دهد . کسی میتونه error کدهای من رو بگیره و یک printscreen از اجرای کد ها برای من قرار بده ؟ ممنون میشم.
DCT:
function dctquant('c:\2.jpg',dx,dy);
% usage : dctquant('h:\el593\exp10\lena.img',256,256); (WYT: please verify)
% Note, dctquant calls subfunctions mask2()
Img=fread(fopen('c:\2.jpg'),[dx,dy]);
colormap(gray(256));
image(Img');
set(gca,'XTick',[],'YTick',[]);
title('Original Image');
truesize;
drawnow
y=blokproc(Img,[8 8],'dct2');
yy=blokproc(y,[8 8],'mask2');
yq=blokproc(yy,[8,8],'idct2');
figure;
colormap(gray(256));
image(yq');
set(gca,'XTick',[],'YTick',[]);
title('Quantized Image');
truesize;
drawnow;
 JPEG:% MATLAB 4.2c JPEG image compression program
% by Scott Teresi, http://www.teresi.us
% March 15-17, 1997
 
% Data Classification and Compression class
% Dr. Salari, Univ. of Toledo
 
% This program compresses an image using the JPEG algorithm
 
% Enter matlab, then type the name of this file (jpeg) to execute it.
% It requires a ".mat" file containing raw black-and-white image data
% stored in matrix variable "X". The matrix contains the pixel intensities.
% Also, store a colormap in variable "map" (see first few lines of program).
 
 
% Initializations
 
clear                  % clear all variables from previous sessions
load lenna             % load file of variables containing a gray image matrix
 
orig_img = X;          % image matrix was stored in variable X
                       % image colormap is stored in variable map
 
quant_multiple = 1;    % set the multiplier to change size of quant. levels
                       % (fractions decrease distortion)
                       % vary quant_mult from .1 to 3 (see jpeg.results file)
 
blocksize = 8;         % set the size of chunks to take the DCT of ( =< 8)
DCT_quantizer = ...    % levels for quantizing the DCT block (8x8 matrix)
        [ 16  11  10  16  24  40  51  61; ...
          12  12  14  19  26  58  60  55; ...
          14  13  16  24  40  57  69  56; ...
          14  17  22  29  51  87  80  62; ...
          18  22  37  56  68 109 103  77; ...
          24  35  55  64  81 104 113  92; ...
          49  64  78  87 103 121 120 101; ...
          72  92  95  98 112 100 103  99 ];
 
sz = size(orig_img);
rows = sz(1,1);               % finds image's rows and columns
cols = sz(1,2);
colors = max(max(orig_img));  % guess at the number of colors in the image
 
% Replace a color colormap with a grayscale one
%
% map_sz = size(map);
% clrs = map_sz(1,1);
% gray_map = (0coffeelrs-1)' / (clrs-1);
% gray_map = [gray_map gray_map gray_map];
% map = gray_map;
% colormap(map)
 
 
 
 
% Introduction
 
str = str2mat( ...
  'Scott Teresi, March 1997.', ...
  'This program implements the JPEG data compression algorithm.');
ssdisp(0, str);
 
fprintf (1, 'Image used:               lenna.mat\n');
fprintf (1, 'Its size is:              %dx%d\n', rows, cols);
fprintf (1, 'Number of colors (guess): %d\n', colors);
fprintf (1, 'DCT block size:           %dx%d\n', blocksize, blocksize);
fprintf (1, 'Quant. size multiplier:   %d\n', quant_multiple);
 
% Display the original image
 
figure(1)
image(orig_img)
colormap(map)
title('Original image')
figure(2)
 
 
 
 
% Prepare image for transform
 
% Level-shift the image (center intensity values around 0)
 
orig_img = orig_img - ceil(colors/2);
 
% Replicate edges of image to make its dimensions a multiple of blocksize
 
pad_cols = (1 - (cols/blocksize - floor(cols/blocksize))) * blocksize;
if pad_cols == blocksize, pad_cols = 0; end
pad_rows = (1 - (rows/blocksize - floor(rows/blocksize))) * blocksize;
if pad_rows == blocksize, pad_rows = 0; end
 
for extra_cols = 1:pad_cols
  orig_img(1:rows, cols+extra_cols) = orig_img(1:rows, cols);
end
 
cols = cols + pad_cols;    % orig_img is now pad_cols wider
 
for extra_rows = 1:pad_rows
  orig_img(rows+extra_rows, 1coffeeols) = orig_img(rows, 1coffeeols);
end
 
rows = rows + pad_rows;    % orig_img is now pad_rows taller
 
 
 
 
% calculate the DCT transform matrix
%    (from page 336 of the Intro to Data Compression book)
 
i = 0;
for j = 0: blocksize - 1
  DCT_trans(i + 1, j + 1) = sqrt(1 / blocksize) ...
                          * cos ((2 * j + 1) * i * pi / (2 * blocksize));
end
 
for i = 1: blocksize - 1
  for j = 0: blocksize - 1
    DCT_trans(i + 1, j + 1) = sqrt(2 / blocksize) ...
                            * cos ((2 * j + 1) * i * pi / (2 * blocksize));
  end
end
 
 
 
 
% Take DCT of blocks of size blocksize
 
fprintf(1, '\nFinding the DCT and quantizing...\n');
starttime = cputime;              % "cputime" is an internal cpu time counter
 
jpeg_img = orig_img - orig_img;   % zero the matrix for the compressed image
 
for row = 1: blocksize: rows
  for col = 1: blocksize: cols
 
       % take a block of the image:
    DCT_matrix = orig_img(row: row + blocksize-1, col: col + blocksize-1);
 
       % perform the transform operation on the 2-D block
       %    (from page 331 of the Intro to Data Compression book)
    DCT_matrix = DCT_trans * DCT_matrix * DCT_trans';
 
       % quantize it (levels stored in DCT_quantizer matrix):
    DCT_matrix = floor (DCT_matrix ...
          ./ (DCT_quantizer(1:blocksize, 1:blocksize) * quant_multiple) + 0.5);
 
       % place it into the compressed-image matrix:
    jpeg_img(row: row + blocksize-1, col: col + blocksize-1) = DCT_matrix;
 
  end
end
 
fprintf(1, '   CPU time used: %1.3f\n', (cputime - starttime))
 
 
 
 
% Reverse the process (take the Inverse DCT)
 
fprintf(1, 'Reconstructing quantized values and taking the inverse DCT...\n');
starttime = cputime;
 
recon_img = orig_img - orig_img;  % zero the matrix for the reconstructed image
 
for row = 1: blocksize: rows
  for col = 1: blocksize: cols
 
       % take a block of the image:
    IDCT_matrix = jpeg_img(row: row + blocksize-1, col: col + blocksize-1);
 
       % reconstruct the quantized values:
    IDCT_matrix = IDCT_matrix ...
                .* (DCT_quantizer(1:blocksize, 1:blocksize) * quant_multiple);
 
       % perform the inverse DCT:
    IDCT_matrix = DCT_trans' * IDCT_matrix * DCT_trans;
 
       % place it into the reconstructed image:
    recon_img(row: row + blocksize-1, col: col + blocksize-1) = IDCT_matrix;
 
  end
end
 
fprintf(1, '   CPU time used: %1.3f\n', (cputime - starttime))
 
 
 
 
% Restore image to normal
 
% Level-shift the image back
 
recon_img = recon_img + ceil(colors/2);
orig_img = orig_img + ceil(colors/2);
 
% Clip off padded rows and columns
 
rows = rows - pad_rows;
cols = cols - pad_cols;
recon_img = recon_img(1:rows, 1coffeeols);
 
% Display image
 
colormap(map)
image(recon_img)
title('Decompressed JPEG image')
 
 
 
 
% Calculate signal-to-noise ratio
 
fprintf(1, 'Finding the signal-to-noise ratio...\n');
starttime = cputime;
 
PSNR = 0;
for row = 1:rows
  for col = 1coffeeols
    PSNR = PSNR + (orig_img(row, col) - recon_img(row, col)) ^ 2;
  end
end
PSNR = 10 * log10 ((255^2) / (1 / (((rows + cols) / 2) ^ 2) * PSNR));
             % (averaged rows and cols together)
 
fprintf(1, '   CPU time used: %1.3f\n', (cputime - starttime))
fprintf(1, '\nThe signal-to-noise ratio (PSNR) is: %1.3f dB\n\n', PSNR);
 
 
 
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