|
/Users/lyon/j4p/src/ip/transforms/Gauss.java
|
1 package ip.transforms;
2
3 import math.Mat2;
4
5 /**
6 * User: lyon
7 * Date: Dec 22, 2002
8 * Time: 1:53:40 AM
9 */
10 public class Gauss {
11
12 public static final double gauss(
13 double x, double y,
14 double xc, double yc, double sigma) {
15 double dx = x - xc;
16 double dy = y - yc;
17 double dx2 = dx * dx;
18 double dy2 = dy * dy;
19 double sigma2 = sigma * sigma;
20 double oneOnSigma2 = 1 / sigma2;
21 return
22 Math.exp(-(dx2 + dy2) *
23 oneOnSigma2 / 2) / Math.PI * oneOnSigma2 / 2;
24 }
25
26 public static final double gauss(
27 double x,
28 double xc, double sigma) {
29 double oneOnSigmaSquaredOn2 = 1 / (sigma * sigma) / 2;
30 return
31 Math.exp(-((x - xc) * (x - xc)) *
32 oneOnSigmaSquaredOn2) / Math.PI * oneOnSigmaSquaredOn2;
33 }
34
35 public static void printGaussKernel(
36 int M, int N,
37 double sigma, double centerMax) {
38 short k[][] = new short[M][N];
39 int xc = M / 2;
40 int yc = N / 2;
41 double scale = centerMax * 2 * Math.PI * sigma * sigma;
42 for (int x = 0; x < k.length; x++)
43 for (int y = 0; y < k[0].length; y++)
44 k[x][y] = (short)
45 (scale * gauss(x, y, xc, yc, sigma));
46 //Mat.printKernel(k,"gauss"+k.length);
47 }
48
49 public static void printGaussKernel(
50 int M, int N,
51 double sigma) {
52 float k[][] = getGaussKernel(M, N, sigma);
53 Mat2.printKernel(k, "gauss" + k.length);
54 }
55
56 public static float[][] getGaussKernel(
57 int M, int N,
58 double sigma) {
59 float k[][] = new float[M][N];
60 int xc = M / 2;
61 int yc = N / 2;
62 for (int x = 0; x < k.length; x++)
63 for (int y = 0; y < k[0].length; y++)
64 k[x][y] = (float) gauss(x, y, xc, yc, sigma);
65 Mat2.normalize(k);
66 return k;
67 }
68
69 public static double getMagnitudeOfTheDerivativeOfGauss(
70 double x, double y,
71 double xc, double yc, double sigma) {
72 ConvolutionUtils.t2 = Math.pow(2.0 * x - 2.0 * xc, 2.0);
73 ConvolutionUtils.t3 = sigma * sigma;
74 ConvolutionUtils.t4 = ConvolutionUtils.t3 * ConvolutionUtils.t3;
75 ConvolutionUtils.t5 = ConvolutionUtils.t4 * ConvolutionUtils.t4;
76 ConvolutionUtils.t6 = 1 / ConvolutionUtils.t5;
77 ConvolutionUtils.t9 = Math.pow(x - xc, 2.0);
78 ConvolutionUtils.t11 = Math.pow(y - yc, 2.0);
79 ConvolutionUtils.t16 = Math.pow(Math.exp(-(ConvolutionUtils.t9 + ConvolutionUtils.t11) / ConvolutionUtils.t3 / 2), 2.0);
80 ConvolutionUtils.t17 = Math.PI * Math.PI;
81 ConvolutionUtils.t19 = ConvolutionUtils.t16 / ConvolutionUtils.t17;
82 ConvolutionUtils.t22 = Math.pow(2.0 * y - 2.0 * yc, 2.0);
83 double ddx = ConvolutionUtils.t2 * ConvolutionUtils.t6 * ConvolutionUtils.t19;
84 double ddy = ConvolutionUtils.t22 * ConvolutionUtils.t6 * ConvolutionUtils.t19;
85 ConvolutionUtils.t26 = Math.sqrt(ddx + ddy);
86 ConvolutionUtils.t27 = ConvolutionUtils.t26 / 4;
87 return ConvolutionUtils.t27;
88 }
89
90 public static void printMagnitudeOfTheDerivativeOfGauss(
91 int M, int N,
92 double sigma) {
93 float k[][] = getMagnitudeOfTheDerivativeOfGauss(M, N, sigma);
94 //Mat.printKernel(k,"MagnitudeOfTheDerivativeOfGauss"+k.length);
95 }
96
97 public static float[][] getMagnitudeOfTheDerivativeOfGauss(
98 int M, int N,
99 double sigma) {
100 float k[][] = new float[M][N];
101 int xc = M / 2;
102 int yc = N / 2;
103 for (int x = 0; x < k.length; x++)
104 for (int y = 0; y < k[0].length; y++)
105 k[x][y] = (float)
106 getMagnitudeOfTheDerivativeOfGauss(x, y, xc, yc, sigma);
107 Mat2.normalize(k);
108 return k;
109 }
110
111 public static float[][] getGauss3() {
112 float k[][] = {
113 {1, 2, 1},
114 {2, 4, 2},
115 {1, 2, 1}
116 };
117 Mat2.scale(k, 1 / 16.0);
118 return k;
119 }
120
121 public static float[][] getGauss7() {
122 float k [][] = {
123
124 {1, 1, 2, 2, 2, 1, 1},
125 {1, 2, 2, 4, 2, 2, 1},
126 {2, 2, 4, 8, 4, 2, 2},
127 {2, 4, 8, 16, 8, 4, 2},
128 {2, 2, 4, 8, 4, 2, 2},
129 {1, 2, 2, 4, 2, 2, 1},
130 {1, 1, 2, 2, 2, 1, 1}
131 };
132 Mat2.normalize(k);
133 return k;
134 }
135
136 public static float[][] getGauss15() {
137 float k[][] = {
138 {1.9045144E-7f, 9.671922E-7f, 3.8253193E-6f, 1.1782813E-5f, 2.8265502E-5f, 5.2806907E-5f, 7.6833596E-5f, 8.7063876E-5f, 7.6833596E-5f, 5.2806907E-5f, 2.8265502E-5f, 1.1782813E-5f, 3.8253193E-6f, 9.671922E-7f, 1.9045144E-7f},
139 {9.671922E-7f, 4.9118075E-6f, 1.9426576E-5f, 5.9838065E-5f, 1.4354405E-4f, 2.681756E-4f, 3.901932E-4f, 4.4214682E-4f, 3.901932E-4f, 2.681756E-4f, 1.4354405E-4f, 5.9838065E-5f, 1.9426576E-5f, 4.9118075E-6f, 9.671922E-7f},
140 {3.8253193E-6f, 1.9426576E-5f, 7.6833596E-5f, 2.3666414E-4f, 5.677278E-4f, 0.0010606551f, 0.001543244f, 0.0017487246f, 0.001543244f, 0.0010606551f, 5.677278E-4f, 2.3666414E-4f, 7.6833596E-5f, 1.9426576E-5f, 3.8253193E-6f},
141 {1.1782813E-5f, 5.9838065E-5f, 2.3666414E-4f, 7.2897685E-4f, 0.0017487246f, 0.0032670477f, 0.0047535263f, 0.0053864513f, 0.0047535263f, 0.0032670477f, 0.0017487246f, 7.2897685E-4f, 2.3666414E-4f, 5.9838065E-5f, 1.1782813E-5f},
142 {2.8265502E-5f, 1.4354405E-4f, 5.677278E-4f, 0.0017487246f, 0.004194972f, 0.00783724f, 0.011403117f, 0.012921424f, 0.011403117f, 0.00783724f, 0.004194972f, 0.0017487246f, 5.677278E-4f, 1.4354405E-4f, 2.8265502E-5f},
143 {5.2806907E-5f, 2.681756E-4f, 0.0010606551f, 0.0032670477f, 0.00783724f, 0.014641892f, 0.021303825f, 0.024140399f, 0.021303825f, 0.014641892f, 0.00783724f, 0.0032670477f, 0.0010606551f, 2.681756E-4f, 5.2806907E-5f},
144 {7.6833596E-5f, 3.901932E-4f, 0.001543244f, 0.0047535263f, 0.011403117f, 0.021303825f, 0.030996885f, 0.03512407f, 0.030996885f, 0.021303825f, 0.011403117f, 0.0047535263f, 0.001543244f, 3.901932E-4f, 7.6833596E-5f},
145 {8.7063876E-5f, 4.4214682E-4f, 0.0017487246f, 0.0053864513f, 0.012921424f, 0.024140399f, 0.03512407f, 0.039800785f, 0.03512407f, 0.024140399f, 0.012921424f, 0.0053864513f, 0.0017487246f, 4.4214682E-4f, 8.7063876E-5f},
146 {7.6833596E-5f, 3.901932E-4f, 0.001543244f, 0.0047535263f, 0.011403117f, 0.021303825f, 0.030996885f, 0.03512407f, 0.030996885f, 0.021303825f, 0.011403117f, 0.0047535263f, 0.001543244f, 3.901932E-4f, 7.6833596E-5f},
147 {5.2806907E-5f, 2.681756E-4f, 0.0010606551f, 0.0032670477f, 0.00783724f, 0.014641892f, 0.021303825f, 0.024140399f, 0.021303825f, 0.014641892f, 0.00783724f, 0.0032670477f, 0.0010606551f, 2.681756E-4f, 5.2806907E-5f},
148 {2.8265502E-5f, 1.4354405E-4f, 5.677278E-4f, 0.0017487246f, 0.004194972f, 0.00783724f, 0.011403117f, 0.012921424f, 0.011403117f, 0.00783724f, 0.004194972f, 0.0017487246f, 5.677278E-4f, 1.4354405E-4f, 2.8265502E-5f},
149 {1.1782813E-5f, 5.9838065E-5f, 2.3666414E-4f, 7.2897685E-4f, 0.0017487246f, 0.0032670477f, 0.0047535263f, 0.0053864513f, 0.0047535263f, 0.0032670477f, 0.0017487246f, 7.2897685E-4f, 2.3666414E-4f, 5.9838065E-5f, 1.1782813E-5f},
150 {3.8253193E-6f, 1.9426576E-5f, 7.6833596E-5f, 2.3666414E-4f, 5.677278E-4f, 0.0010606551f, 0.001543244f, 0.0017487246f, 0.001543244f, 0.0010606551f, 5.677278E-4f, 2.3666414E-4f, 7.6833596E-5f, 1.9426576E-5f, 3.8253193E-6f},
151 {9.671922E-7f, 4.9118075E-6f, 1.9426576E-5f, 5.9838065E-5f, 1.4354405E-4f, 2.681756E-4f, 3.901932E-4f, 4.4214682E-4f, 3.901932E-4f, 2.681756E-4f, 1.4354405E-4f, 5.9838065E-5f, 1.9426576E-5f, 4.9118075E-6f, 9.671922E-7f},
152 {1.9045144E-7f, 9.671922E-7f, 3.8253193E-6f, 1.1782813E-5f, 2.8265502E-5f, 5.2806907E-5f, 7.6833596E-5f, 8.7063876E-5f, 7.6833596E-5f, 5.2806907E-5f, 2.8265502E-5f, 1.1782813E-5f, 3.8253193E-6f, 9.671922E-7f, 1.9045144E-7f}};
153 //sum=0.9999999983459134
154 return k;
155 }
156 }
157