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.image.FImage;
33 import org.openimaj.image.processor.SinglebandImageProcessor;
34
35 import edu.emory.mathcs.jtransforms.fft.FloatFFT_2D;
36
37 /**
38 * From the matlab implementation of DISCGAUSSFFT which uses an FFT to apply a gaussian kernel.
39 * The matlab docs:
40 *
41 % DISCGAUSSFFT(pic, sigma2) -- Convolves an image by the
42 % (separable) discrete analogue of the Gaussian kernel by
43 % performing the convolution in the Fourier domain.
44 % The parameter SIGMA2 is the variance of the kernel.
45
46 % Reference: Lindeberg "Scale-space theory in computer vision", Kluwer, 1994.
47 *
48 * @author Sina Samangooei (ss@ecs.soton.ac.uk)
49 *
50 */
51 public class FDiscGausConvolve implements SinglebandImageProcessor<Float, FImage> {
52 private float sigma2;
53
54 /**
55 * Construct with given variance
56 * @param sigma2 variance of the kernel
57 */
58 public FDiscGausConvolve(float sigma2) {
59 this.sigma2 = sigma2;
60 // this.fft = new FastFourierTransformer();
61 }
62
63 @Override
64 public void processImage(FImage image) {
65 int cs = image.getCols();
66 int rs = image.getRows();
67 FloatFFT_2D fft = new FloatFFT_2D(rs,cs);
68 float[][] prepared = new float[rs][cs*2];
69 for(int r = 0; r < rs ; r++){
70 for(int c = 0; c < cs; c++){
71 prepared[r][c*2] = image.pixels[r][c];
72 prepared[r][1 + c*2] = 0;
73 }
74 }
75 fft.complexForward(prepared);
76 for(int y = 0; y < rs; y++){
77 for(int x = 0; x < cs; x++){
78 double xcos = Math.cos(2 * Math.PI * ((float)x/cs));
79 double ycos = Math.cos(2 * Math.PI * ((float)y/rs));
80 float multiply = (float) Math.exp(sigma2 * (xcos + ycos - 2));
81 prepared[y][x*2] = prepared[y][x*2] * multiply;
82 prepared[y][1 + x*2] = prepared[y][1 + x*2] * multiply;
83 }
84 }
85 fft.complexInverse(prepared, true);
86 for(int r = 0; r < rs ; r++){
87 for(int c = 0; c < cs; c++){
88 image.pixels[r][c] = prepared[r][c*2];
89 }
90 }
91 }
92 }