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.PI;
33 import static java.lang.Math.exp;
34
35 import org.openimaj.image.FImage;
36 import org.openimaj.math.util.FloatArrayStatsUtils;
37
38 /**
39 * 2D Laplacian of Gaussian filter
40 *
41 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
42 */
43 public class LaplacianOfGaussian2D extends FConvolution {
44 /**
45 * Construct with given kernel size and variance.
46 * @param width kernel width
47 * @param height kernel height
48 * @param sigma variance
49 */
50 public LaplacianOfGaussian2D(int width, int height, float sigma) {
51 super(createKernelImage(width, height, sigma));
52 }
53
54 /**
55 * Construct with given kernel size and variance.
56 * @param size kernel width/height
57 * @param sigma variance
58 */
59 public LaplacianOfGaussian2D(int size, float sigma) {
60 super(createKernelImage(size, size, sigma));
61 }
62
63 /**
64 * Create a kernel image with given kernel size and variance.
65 * @param size image height/width.
66 * @param sigma variance.
67 * @return new kernel image.
68 */
69 public static FImage createKernelImage(int size, float sigma) {
70 return createKernelImage(size, size, sigma);
71 }
72
73 /**
74 * Create a kernel image with given kernel size and variance.
75 * @param width image width.
76 * @param height image height.
77 * @param sigma variance.
78 * @return new kernel image.
79 */
80 public static FImage createKernelImage(int width, int height, float sigma) {
81 FImage f = new FImage(width, height);
82 int hw = (width-1)/2;
83 int hh = (height-1)/2;
84 float sigmasq = sigma * sigma;
85 float sigma4 = sigmasq*sigmasq;
86
87 for (int y=-hh, j=0; y<hh; y++, j++) {
88 for (int x=-hw, i=0; x<hw; x++, i++) {
89 int radsqrd = x*x + y*y;
90 f.pixels[j][i] = (float) (-1 / (PI*sigma4)*(1-radsqrd/(2*sigmasq))*exp(-radsqrd/(2*sigmasq)));
91 }
92 }
93 return f.subtractInplace(FloatArrayStatsUtils.mean(f.pixels));
94 }
95 }