wm_bruyn_e.c

包含了多个matlab编程在图像中加入水印的处理代码

    double mean_1A, mean_1B, mean_2A, mean_2B, mean_1, mean_2;
    double mean__1A, mean__1B, mean__2A, mean__2B;
    int n_1A, n_1B, n_2A, n_2B, n_1, n_2;
    int var_1A, var_1B, var_2A, var_2B;
    int zone1_ok, zone2_ok;

    // find an unused block randomly, depending on seed
    do {
      xb = random() % (cols / blocksize);
      yb = random() % (rows / blocksize);
    } while (add_coord(coords, xb, yb) < 0);

    // copy image block
    copy_grays_to_block(block, image, xb * blocksize, yb * blocksize, blocksize, blocksize);    

    if (verbose > 0)
      fprintf(stderr, "embedding bit #%d (= %d) in block at (%d/%d)\n", n, get_signature_bit(n), xb * blocksize, yb * blocksize);
    if (verbose > 8) {
      print_grays(image, xb * blocksize, yb * blocksize, blocksize, blocksize);
      fprintf(stderr, "\n");
    }

    // sort luminance values in block to represent increasing function F
    sort_grays(block[0], n_block);

    if (verbose > 8) {
      print_grays(block, 0, 0, blocksize, blocksize);
      fprintf(stderr, "\n");
    }

    // calculate slopes of F and determine smax, the max. slope of F
    // the index where smax occures is called alpha
    alpha = 0;
    smax = 0.0;
    for (i = 0; i < n_block - 1; i++) {
      slope[i] = block[0][i + 1] - block[0][i];
      if (slope[i] > smax) {
        smax = slope[i];
        alpha = i;
      }
    }
    slope[n_block - 1] = 0;

    // block type classification
    blocktype = BLOCKTYPE_UNKNOWN;

    if (smax < threshold_noise) {
      // block has noise contrast
     
       blocktype = BLOCKTYPE_NOISE;
      beta_minus = beta_plus = alpha;
    }
    else {
      // block has progressive or hard contrast, let's find out...

      beta_minus = alpha - 1;
      while (beta_minus >= 0 && smax - slope[beta_minus] <= threshold_slope)
        beta_minus--;

      beta_plus = alpha + 1;
      while (beta_plus < n_block && smax - slope[beta_plus] <= threshold_slope)
        beta_plus++;

      if (beta_minus + 1 == alpha && beta_plus - 1 == alpha)
        blocktype = BLOCKTYPE_HARD;
      else 
        blocktype = BLOCKTYPE_PROGRESSIVE;
    }

    if (verbose > 1) {
      fprintf(stderr, "blocktype: %d\n", blocktype); 
      fprintf(stderr, "Smax = %lf, alpha = %d, beta- = %d, beta+ = %d\n", smax, alpha, beta_minus, beta_plus);
    }

    // block pixel classification
    for (i = 0; i < blocksize; i++)
      for (j = 0; j < blocksize; j++) {
        gray pixel = image[yb * blocksize + j][xb * blocksize + i];
        zone[j][i] = ZONE_VOID;
        switch (blocktype) {
          case BLOCKTYPE_PROGRESSIVE:
          case BLOCKTYPE_HARD:
            if (pixel < block[0][beta_minus])
              zone[j][i] = ZONE_1;  
            else if (pixel > block[0][beta_plus])
              zone[j][i] = ZONE_2;  
            break;
          case BLOCKTYPE_NOISE:
            if (pixel < block[0][n_block / 2])
              zone[j][i] = ZONE_1;
            else if (pixel > block[0][n_block / 2])
              zone[j][i] = ZONE_2;
            break;
          default:
            fprintf(stderr, "%s: invalid block type\n", progname);
            break;
        }
      }
 
    if (verbose > 8) {
      print_grays(zone, 0, 0, blocksize, blocksize);
      fprintf(stderr, "\n");
    }

    // calculate mean values for zone/categories
    mean_1A = mean_1B = mean_2A = mean_2B = mean_1 = mean_2 = 0.0;
    n_1A = n_1B = n_2A = n_2B = n_1 = n_2 = 0;
    for (i = 0; i < blocksize; i++)
      for (j = 0; j < blocksize; j++) {
        gray pixel = image[yb * blocksize + j][xb * blocksize + i];
        int pixel_zone = zone[j][i];
        int pixel_category = CATEGORY_VOID;
        if (pixel_zone == ZONE_1)
          pixel_category = category1[j][i];
        else if (pixel_zone == ZONE_2)
          pixel_category = category2[j][i];

        switch (pixel_zone | pixel_category) {
          case CLASSIFICATION_1A:
            n_1++;
            n_1A++;
            mean_1A += pixel;
            mean_1 += pixel;
            break;
          case CLASSIFICATION_1B:
            n_1++;
            n_1B++;
            mean_1B += pixel;
            mean_1 += pixel;
            break;
          case CLASSIFICATION_2A:
            n_2++;
            n_2A++;
            mean_2A += pixel;
            mean_2 += pixel;
            break;
          case CLASSIFICATION_2B:
            n_2++;
            n_2B++;
            mean_2B += pixel;
            mean_2 += pixel;
            break;
        }
      }

    if (n_1 && n_1A && n_1B) {
      mean_1 /= (double) n_1;
      mean_1A /= (double) n_1A;
      mean_1B /= (double) n_1B;
      zone1_ok = 1;
    }
    else {
      mean_1 = mean_1A = mean_1B = 0.0;
      zone1_ok = 0;
      if (verbose > 0)
        fprintf(stderr, "zone 1 unusable\n");
    }
    
    if (n_2 && n_2A && n_2B) {
      mean_2 /= (double) n_2;
      mean_2A /= (double) n_2A;
      mean_2B /= (double) n_2B;
      zone2_ok = 1;
    }
    else {
      mean_2 = mean_2A = mean_2B = 0.0;
      zone2_ok = 0;
      if (verbose > 0)
        fprintf(stderr, "zone 2 unusable\n");
    }

    if (!skipping && !zone1_ok && !zone2_ok) {
      // pathological case - can it ever happen?
      if (verbose > 0)
        fprintf(stderr, "block skipped\n");
      continue;
    }

    if (verbose > 2) {
      fprintf(stderr, "m_1 = %lf, m_1A = %lf, m_1B = %lf\n", mean_1, mean_1A, mean_1B);
      fprintf(stderr, "m_2 = %lf, m_2A = %lf, m_2B = %lf\n", mean_2, mean_2A, mean_2B);
    }

    // calculate new mean values required by embedding rule
    if (get_signature_bit(n)) {
      if (zone1_ok) {
        mean__1A = (mean_1 * (double) (n_1A + n_1B) + (double) n_1B * quality) / (double) (n_1A + n_1B);
        mean__1B = mean__1A - quality;
      }
      if (zone2_ok) {
        mean__2A = (mean_2 * (double) (n_2A + n_2B) + (double) n_2B * quality) /  (double) (n_2A + n_2B);
        mean__2B = mean__2A - quality;
      }
    }
    else {
      if (zone1_ok) {
        mean__1A = (mean_1 * (double) (n_1A + n_1B) - (double) n_1B * quality) / (double) (n_1A + n_1B);
        mean__1B = mean__1A + quality;
      }
      if (zone2_ok) {
        mean__2A = (mean_2 * (double) (n_2A + n_2B) - (double) n_2B * quality) / (double) (n_2A + n_2B);
        mean__2B = mean__2A + quality; 
      }
    }

    // calculate luminance variations
    if (zone1_ok) {
      var_1A = rint(mean__1A - mean_1A);
      var_1B = rint(mean__1B - mean_1B);
    }
    else var_1A = var_1B = 0;
    
    if (zone2_ok) {
      var_2A = rint(mean__2A - mean_2A);
      var_2B = rint(mean__2B - mean_2B);
    }
    else var_2A = var_2B = 0;

    if (verbose > 2) {
      if (zone1_ok)
        fprintf(stderr, "m*_1A = %lf, m*_1B = %lf\n", mean__1A, mean__1B);
      if (zone2_ok)
        fprintf(stderr, "m*_2A = %lf, m*_2B = %lf\n", mean__2A, mean__2B);
      fprintf(stderr, "var %d %d %d %d\n", var_1A, var_1B, var_2A, var_2B);
    }

    // apply luminance variations to image pixels
    for (i = 0; i < blocksize; i++)
      for (j = 0; j < blocksize; j++) {
        int pixel = image[yb * blocksize + j][xb * blocksize + i];
        int pixel_zone = zone[j][i];
        int pixel_category = CATEGORY_VOID;
        if (pixel_zone == ZONE_1)
          pixel_category = category1[j][i];
        else if (pixel_zone == ZONE_2)
          pixel_category = category2[j][i];

        switch (pixel_zone | pixel_category) {
          case CLASSIFICATION_1A:
            pixel = GRAYRANGE(pixel + var_1A);
            break;
          case CLASSIFICATION_1B:
            pixel = GRAYRANGE(pixel + var_1B);
            break;
          case CLASSIFICATION_2A:
            pixel = GRAYRANGE(pixel + var_2A);
            break;
          case CLASSIFICATION_2B:
            pixel = GRAYRANGE(pixel + var_2B);
            break;
        }
        image[yb * blocksize + j][xb * blocksize + i] = pixel;
      }

    n++;      
  }

  free_grays(category2);
  free_grays(category1);
  free_grays(zone);
  free_grays(block);

  // write output image dimensions to output file
  pgm_writepgminit(out, cols, rows, maxval, 0);

  // write output image
  for (row = 0; row < rows; row++)
    pgm_writepgmrow(out, image[row], cols, maxval, 0);

  fclose(out);

  pgm_freearray(image, rows);

  exit(0);
}