1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
|
/**
* @author Pacien TRAN-GIRARD
* @author Timothée FLOURE
*/
public final class Filter {
public static final float[][] SMOOTH_CORE = new float[][]{
{0.1f, 0.1f, 0.1f},
{0.1f, 0.2f, 0.1f},
{0.1f, 0.1f, 0.1f}
};
public static final float[][] SOBEL_X_CORE = new float[][]{
{-1, 0, 1},
{-2, 0, 2},
{-1, 0, 1}
};
public static final float[][] SOBEL_Y_CORE = new float[][]{
{-1, -2, -1},
{0, 0, 0},
{1, 2, 1}
};
/**
* Get a pixel without accessing out of bounds
*
* @param gray a HxW float array, H > 0, W > 0
* @param row Y coordinate
* @param col X coordinate
* @return nearest valid pixel color
*/
public static float at(float[][] gray, int row, int col) {
int maxRow = gray.length - 1;
int maxCol = gray[0].length - 1;
if (row < 0) row = 0;
if (col < 0) col = 0;
if (row > maxRow) row = maxRow;
if (col > maxCol) col = maxCol;
return gray[row][col];
}
/**
* Convolve a single-channel image with specified kernel.
*
* @param gray a HxW float array
* @param kernel a MxN float array, with M and N odd
* @return a HxW float array
*/
public static float[][] filter(float[][] gray, float[][] kernel) {
int width = gray[0].length;
int height = gray.length;
float[][] filteredImage = new float[height][width];
for (int row = 0; row < height; ++row) {
for (int col = 0; col < width; ++col) {
float pixelNeighbors[][] = {
{Filter.at(gray, row - 1, col - 1), Filter.at(gray, row - 1, col), Filter.at(gray, row - 1, col + 1)},
{Filter.at(gray, row, col - 1), Filter.at(gray, row, col), Filter.at(gray, row, col + 1)},
{Filter.at(gray, row + 1, col - 1), Filter.at(gray, row + 1, col), Filter.at(gray, row + 1, col + 1)}
};
for (int i = 0; i < kernel[0].length; i++) {
for (int j = 0; j < kernel.length; j++) {
filteredImage[row][col] += kernel[i][j] * pixelNeighbors[i][j];
}
}
}
}
return filteredImage;
}
/**
* Smooth a single-channel image
*
* @param gray a HxW float array
* @return a HxW float array
*/
public static float[][] smooth(float[][] gray) {
return Filter.filter(gray, SMOOTH_CORE);
}
/**
* Compute horizontal Sobel filter
*
* @param gray a HxW float array
* @return a HxW float array
*/
public static float[][] sobelX(float[][] gray) {
return Filter.filter(gray, SOBEL_X_CORE);
}
/**
* Compute vertical Sobel filter
*
* @param gray a HxW float array
* @return a HxW float array
*/
public static float[][] sobelY(float[][] gray) {
return Filter.filter(gray, SOBEL_Y_CORE);
}
/**
* Compute the magnitude of combined Sobel filters
*
* @param gray a HxW float array
* @return a HxW float array
*/
public static float[][] sobel(float[][] gray) {
float[][] x = Filter.sobelX(gray);
float[][] y = Filter.sobelY(gray);
int width = gray[0].length;
int height = gray.length;
float[][] sobelImage = new float[height][width];
for (int row = 0; row < height; ++row) {
for (int col = 0; col < width; ++col) {
sobelImage[row][col] = (float) Math.sqrt(Math.pow(x[row][col], 2) + Math.pow(y[row][col], 2));
}
}
return sobelImage;
}
}
|