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.feature.global;
031
032import org.apache.commons.math.stat.descriptive.SummaryStatistics;
033import org.openimaj.citation.annotation.Reference;
034import org.openimaj.citation.annotation.ReferenceType;
035import org.openimaj.feature.DoubleFV;
036import org.openimaj.feature.FeatureVectorProvider;
037import org.openimaj.image.FImage;
038import org.openimaj.image.analyser.ImageAnalyser;
039import org.openimaj.image.mask.AbstractMaskedObject;
040import org.openimaj.image.processing.convolution.AverageBoxFilter;
041import org.openimaj.image.processing.convolution.Laplacian3x3;
042
043/**
044 * Sharpness measures the clarity and level of detail of an image. This class
045 * measures the variation in sharpness of an image as a function of its
046 * Laplacian, normalized by the local average luminance in the surroundings of
047 * each pixel.
048 * 
049 * @author Jonathon Hare
050 */
051@Reference(
052                type = ReferenceType.Inproceedings,
053                author = { "Jose San Pedro", "Stefan Siersdorfer" },
054                title = "Ranking and Classifying Attractiveness of Photos in Folksonomies",
055                year = "2009",
056                booktitle = "18th International World Wide Web Conference",
057                pages = { "771", "", "771" },
058                url = "http://www2009.eprints.org/78/",
059                month = "April")
060public class SharpnessVariation extends AbstractMaskedObject<FImage>
061                implements
062                ImageAnalyser<FImage>,
063                FeatureVectorProvider<DoubleFV>
064{
065        private final Laplacian3x3 laplacian = new Laplacian3x3();
066        private final AverageBoxFilter average = new AverageBoxFilter(3, 3);
067
068        protected double sharpnessVariation;
069
070        /**
071         * Construct with no mask set
072         */
073        public SharpnessVariation() {
074                super();
075        }
076
077        /**
078         * Construct with a mask.
079         * 
080         * @param mask
081         *            the mask.
082         */
083        public SharpnessVariation(FImage mask) {
084                super(mask);
085        }
086
087        @Override
088        public DoubleFV getFeatureVector() {
089                return new DoubleFV(new double[] { sharpnessVariation });
090        }
091
092        @Override
093        public void analyseImage(FImage image) {
094                final FImage limg = image.process(laplacian);
095                final FImage aimg = image.process(average);
096
097                final SummaryStatistics stats = new SummaryStatistics();
098                for (int r = 0; r < limg.height; r++) {
099                        for (int c = 0; c < limg.width; c++) {
100                                if (mask != null && mask.pixels[r][c] == 0)
101                                        continue;
102
103                                if (aimg.pixels[r][c] != 0) {
104                                        stats.addValue(Math.abs(limg.pixels[r][c] / aimg.pixels[r][c]));
105                                }
106                        }
107                }
108
109                sharpnessVariation = stats.getStandardDeviation();
110        }
111
112        /**
113         * Get the variation in sharpness of the last image processed with
114         * {@link #analyseImage(FImage)}.
115         * 
116         * @return the sharpness variation value
117         */
118        public double getSharpnessVariation() {
119                return sharpnessVariation;
120        }
121}