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1 @c Copyright (C) 1996, 1997, 2007 John W. Eaton |
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2 @c This is part of the Octave manual. |
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3 @c For copying conditions, see the file gpl.texi. |
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4 |
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5 @node Image Processing |
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6 @chapter Image Processing |
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7 |
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8 Since an image basically is a matrix Octave is a very powerful |
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9 environment for processing and analysing images. To illustrate |
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10 how easy it is to do image processing in Octave, the following |
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11 example will load an image, smooth it by a 5-by-5 averaging filter, |
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12 and compute the gradient of the smoothed image. |
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13 |
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14 @example |
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15 I = loadimage ("default.img"); |
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16 S = conv2 (I, ones (5, 5) / 25, "same"); |
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17 [Dx, Dy] = gradient (S); |
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18 @end example |
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19 |
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20 @noindent |
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21 In this example @code{S} contains the smoothed image, and @code{Dx} |
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22 and @code{Dy} contains the partial spatial derivatives of the image. |
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23 |
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24 @menu |
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25 * Loading and Saving Images:: |
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26 * Displaying Images:: |
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27 * Representing Images:: |
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28 * Plotting on top of Images:: |
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29 * Color Conversion:: |
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30 @end menu |
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31 |
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32 @node Loading and Saving Images |
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33 @section Loading and Saving Images |
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34 |
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35 The first step in most image processing tasks is to load an image |
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36 into Octave. Currently Octave only support saving images in the |
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37 Portable Pixmap Format (PPM), PostScript, and Octave's own format, and |
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38 loading images in Octave's format. Most image processing code will |
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39 follow the structure of this code |
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40 |
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41 @example |
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42 I = loadimage ("my_input_image.img"); |
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43 J = process_my_image (I); |
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44 saveimage ("my_output_image.img", J); |
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45 @end example |
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46 |
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47 @DOCSTRING(loadimage) |
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48 |
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49 @DOCSTRING(saveimage) |
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50 |
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51 @DOCSTRING(IMAGE_PATH) |
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52 |
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53 @node Displaying Images |
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54 @section Displaying Images |
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55 |
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56 A natural part of image processing is visualization of an image. |
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57 The most basic function for this is the @code{imshow} function that |
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58 shows the image given in the first input argument. This function uses |
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59 an external program to show the image. If gnuplot 4.2 or later is |
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60 available it will be used to display the image, otherwise the |
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61 @code{display}, @code{xv}, or @code{xloadimage} program is used. The |
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62 actual program can be selected with the @code{image_viewer} function. |
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63 |
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64 @DOCSTRING(imshow) |
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65 |
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66 @DOCSTRING(image) |
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67 |
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68 @DOCSTRING(imagesc) |
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69 |
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70 @DOCSTRING(image_viewer) |
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71 |
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72 @node Representing Images |
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73 @section Representing Images |
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74 |
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75 In general Octave supports four different kinds of images, gray-scale |
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76 images, RGB images, binary images, and indexed images. A gray-scale |
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77 image is represented with an M-by-N matrix in which each |
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78 element corresponds to the intensity of a pixel. An RGB image is |
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79 represented with an M-by-N-by3 array where each |
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80 3-vector corresponds to the red, green, and blue intensities of each |
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81 pixel. |
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82 |
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83 The actual meaning of the value of a pixel in a gray-scale or RGB |
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84 image depends on the class of the matrix. If the matrix is of class |
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85 @code{double} pixel intensities are between 0 and 1, if it is of class |
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86 @code{uint8} intensities are between 0 and 255, and if it is of class |
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87 @code{uint16} intensities are between 0 and 65535. |
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88 |
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89 A binary image is a M-by-N matrix of class @code{logical}. |
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90 A pixel in a binary image is black if it is @code{false} and white |
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91 if it is @code{true}. |
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92 |
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93 An indexed image consists of an M-by-N matrix of integers |
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94 and a C-by-3 color map. Each integer corresponds to an |
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95 index in the color map, and each row in the color map corresponds to |
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96 a RGB color. The color map must be of class @code{double} with values |
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97 between 0 and 1. |
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98 |
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99 @DOCSTRING(gray2ind) |
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100 |
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101 @DOCSTRING(ind2gray) |
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102 |
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103 @DOCSTRING(rgb2ind) |
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104 |
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105 @DOCSTRING(ind2rgb) |
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106 |
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107 @DOCSTRING(colormap) |
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108 |
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109 @DOCSTRING(gray) |
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110 |
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111 @DOCSTRING(ocean) |
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112 |
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113 @node Plotting on top of Images |
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114 @section Plotting on top of Images |
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115 |
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116 If gnuplot is being used to display images it is possible to plot on |
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117 top of images. Since an image is a matrix it is indexed by row and |
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118 column values. The plotting system is, however, based on the |
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119 traditional @math{(x, y)} system. To minimize the difference between |
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120 the two systems Octave places the origin of the coordinate system in |
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121 the point corresponding to the pixel at @math{(1, 1)}. So, to plot |
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122 points given by row and column values on top of an image, one should |
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123 simply call @code{plot} with the column values as the first argument |
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124 and the row values as the second. As an example the following code |
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125 generates an image with random intensities between 0 and 1, and shows |
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126 the image with red circles over pixels with an intensity above |
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127 @math{0.99}. |
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128 |
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129 @example |
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130 I = rand (100, 100); |
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131 [row, col] = find (I > 0.99); |
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132 hold ("on"); |
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133 imshow (I); |
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134 plot (col, row, "ro"); |
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135 hold ("off"); |
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136 @end example |
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137 |
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138 @node Color Conversion |
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139 @section Color Conversion |
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140 |
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141 Octave supports conversion from the RGB color system to NTSC and HSV |
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142 and vice versa. |
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143 |
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144 @DOCSTRING(rgb2hsv) |
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145 |
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146 @DOCSTRING(hsv2rgb) |
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147 |
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148 @DOCSTRING(rgb2ntsc) |
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149 |
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150 @DOCSTRING(ntsc2rgb) |
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151 |
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152 |
