1 /**
2 * Copyright (c) 2011, The University of Southampton and the individual contributors.
3 * All rights reserved.
4 *
5 * Redistribution and use in source and binary forms, with or without modification,
6 * are permitted provided that the following conditions are met:
7 *
8 * * Redistributions of source code must retain the above copyright notice,
9 * this list of conditions and the following disclaimer.
10 *
11 * * Redistributions in binary form must reproduce the above copyright notice,
12 * this list of conditions and the following disclaimer in the documentation
13 * and/or other materials provided with the distribution.
14 *
15 * * Neither the name of the University of Southampton nor the names of its
16 * contributors may be used to endorse or promote products derived from this
17 * software without specific prior written permission.
18 *
19 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
20 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
21 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
22 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
23 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
24 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
25 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
26 * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
27 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
28 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
29 */
30 package org.openimaj.image.processing.convolution;
31
32 import static java.lang.Math.exp;
33
34 import org.openimaj.image.FImage;
35 import org.openimaj.math.util.FloatArrayStatsUtils;
36
37 /**
38 * Simple 2D Gaussian convolution. In most cases the {@link FGaussianConvolve}
39 * filter will do the same thing, but much much faster!
40 *
41 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
42 *
43 */
44 public class Gaussian2D extends FConvolution {
45
46 /**
47 * Construct with given kernel size and variance.
48 *
49 * @param width
50 * kernel width
51 * @param height
52 * kernel height
53 * @param sigma
54 * variance
55 */
56 public Gaussian2D(int width, int height, float sigma) {
57 super(createKernelImage(width, height, sigma));
58 }
59
60 /**
61 * Construct with given kernel size and variance.
62 *
63 * @param size
64 * kernel width/height
65 * @param sigma
66 * standard deviation
67 */
68 public Gaussian2D(int size, float sigma) {
69 super(createKernelImage(size, size, sigma));
70 }
71
72 /**
73 * Create a kernel image with given kernel size and standard deviation.
74 *
75 * @param size
76 * image height/width.
77 * @param sigma
78 * standard deviation.
79 * @return new kernel image.
80 */
81 public static FImage createKernelImage(int size, float sigma) {
82 return createKernelImage(size, size, sigma);
83 }
84
85 /**
86 * Create a kernel image with given kernel size and standard deviation.
87 *
88 * @param width
89 * image width.
90 * @param height
91 * image height.
92 * @param sigma
93 * standard deviation.
94 * @return new kernel image.
95 */
96 public static FImage createKernelImage(int width, int height, float sigma) {
97 final FImage f = new FImage(width, height);
98 final int hw = (width - 1) / 2;
99 final int hh = (height - 1) / 2;
100 final float sigmasq = sigma * sigma;
101
102 for (int y = -hh, j = 0; y <= hh; y++, j++) {
103 for (int x = -hw, i = 0; x <= hw; x++, i++) {
104 final int radsqrd = x * x + y * y;
105 f.pixels[j][i] = (float) exp(-radsqrd / (2 * sigmasq));
106 }
107 }
108 final float sum = FloatArrayStatsUtils.sum(f.pixels);
109 return f.divideInplace(sum);
110 }
111 }