001/**
002 * Copyright (c) 2011, The University of Southampton and the individual contributors.
003 * All rights reserved.
004 *
005 * Redistribution and use in source and binary forms, with or without modification,
006 * are permitted provided that the following conditions are met:
007 *
008 *   *  Redistributions of source code must retain the above copyright notice,
009 *      this list of conditions and the following disclaimer.
010 *
011 *   *  Redistributions in binary form must reproduce the above copyright notice,
012 *      this list of conditions and the following disclaimer in the documentation
013 *      and/or other materials provided with the distribution.
014 *
015 *   *  Neither the name of the University of Southampton nor the names of its
016 *      contributors may be used to endorse or promote products derived from this
017 *      software without specific prior written permission.
018 *
019 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
020 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
021 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
022 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
023 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
024 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
025 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
026 * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
027 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
028 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
029 */
030package org.openimaj.image.processing.convolution;
031
032import static java.lang.Math.exp;
033
034import org.openimaj.image.FImage;
035import org.openimaj.math.util.FloatArrayStatsUtils;
036
037/**
038 * Simple 2D Gaussian convolution. In most cases the {@link FGaussianConvolve}
039 * filter will do the same thing, but much much faster!
040 *
041 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
042 *
043 */
044public class Gaussian2D extends FConvolution {
045
046        /**
047         * Construct with given kernel size and variance.
048         *
049         * @param width
050         *            kernel width
051         * @param height
052         *            kernel height
053         * @param sigma
054         *            variance
055         */
056        public Gaussian2D(int width, int height, float sigma) {
057                super(createKernelImage(width, height, sigma));
058        }
059
060        /**
061         * Construct with given kernel size and variance.
062         *
063         * @param size
064         *            kernel width/height
065         * @param sigma
066         *            standard deviation
067         */
068        public Gaussian2D(int size, float sigma) {
069                super(createKernelImage(size, size, sigma));
070        }
071
072        /**
073         * Create a kernel image with given kernel size and standard deviation.
074         *
075         * @param size
076         *            image height/width.
077         * @param sigma
078         *            standard deviation.
079         * @return new kernel image.
080         */
081        public static FImage createKernelImage(int size, float sigma) {
082                return createKernelImage(size, size, sigma);
083        }
084
085        /**
086         * Create a kernel image with given kernel size and standard deviation.
087         *
088         * @param width
089         *            image width.
090         * @param height
091         *            image height.
092         * @param sigma
093         *            standard deviation.
094         * @return new kernel image.
095         */
096        public static FImage createKernelImage(int width, int height, float sigma) {
097                final FImage f = new FImage(width, height);
098                final int hw = (width - 1) / 2;
099                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}