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 org.openimaj.citation.annotation.Reference;
33 import org.openimaj.citation.annotation.ReferenceType;
34 import org.openimaj.image.FImage;
35 import org.openimaj.image.processor.SinglebandImageProcessor;
36
37 /**
38 * Fast approximate Gaussian smoothing using repeated fast box filtering.
39 *
40 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
41 *
42 */
43 @Reference(
44 type = ReferenceType.Inproceedings,
45 author = { "Kovesi, P." },
46 title = "Fast Almost-Gaussian Filtering",
47 year = "2010",
48 booktitle = "Digital Image Computing: Techniques and Applications (DICTA), 2010 International Conference on",
49 pages = { "121", "125" },
50 month = "Dec",
51 customData = {
52 "keywords", "Gaussian processes;approximation theory;band-pass filters;image processing;Gaussian bandpass filters;fast almost-Gaussian filtering;image averaging;integral images;log-Gabor filters;separable moving average filters;summed area tables;symmetric transfer function;Approximation methods;Bandwidth;Computer vision;Frequency domain analysis;Laplace equations;Pixel;Transfer functions;Difference of Gaussian filtering;Gaussian smoothing",
53 "doi", "10.1109/DICTA.2010.30"
54 })
55 public class FFastGaussianConvolve implements SinglebandImageProcessor<Float, FImage> {
56 private final int n;
57 private final int m;
58 private SinglebandImageProcessor<Float, FImage> wlBox;
59 private SinglebandImageProcessor<Float, FImage> wuBox;
60
61 /**
62 * Construct an {@link FFastGaussianConvolve} to approximate blurring with a
63 * Gaussian of standard deviation sigma.
64 *
65 * @param sigma
66 * Standard deviation of the approximated Gaussian
67 * @param n
68 * Number of filtering iterations to perform (usually between 3
69 * and 6)
70 */
71 public FFastGaussianConvolve(float sigma, int n) {
72 if (sigma < 1.8) {
73 // std.devs of less than 1.8 are not well approximated.
74 this.m = 1;
75 this.n = 1;
76 this.wlBox = new FGaussianConvolve(sigma);
77 } else {
78 final float ss = sigma * sigma;
79 final double wIdeal = Math.sqrt((12.0 * ss / n) + 1.0);
80 final int wl = (((int) wIdeal) % 2 == 0) ? (int) wIdeal - 1 : (int) wIdeal;
81 final int wu = wl + 2;
82
83 this.n = n;
84 this.m = Math.round((12 * ss - n * wl * wl - 4 * n * wl - 3 * n) / (-4 * wl - 4));
85
86 this.wlBox = new AverageBoxFilter(wl);
87 this.wuBox = new AverageBoxFilter(wu);
88 }
89 }
90
91 @Override
92 public void processImage(FImage image) {
93 for (int i = 0; i < m; i++)
94 wlBox.processImage(image);
95 for (int i = 0; i < n - m; i++)
96 wuBox.processImage(image);
97 }
98 }