/**
 * Copyright (c) 2011, The University of Southampton and the individual contributors.
 * All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without modification,
 * are permitted provided that the following conditions are met:
 *
 *   *  Redistributions of source code must retain the above copyright notice,
 *      this list of conditions and the following disclaimer.
 *
 *   *  Redistributions in binary form must reproduce the above copyright notice,
 *      this list of conditions and the following disclaimer in the documentation
 *      and/or other materials provided with the distribution.
 *
 *   *  Neither the name of the University of Southampton nor the names of its
 *      contributors may be used to endorse or promote products derived from this
 *      software without specific prior written permission.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
 * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 */
package org.openimaj.image.feature.global;

import org.openimaj.feature.DoubleFV;
import org.openimaj.feature.FeatureVectorProvider;
import org.openimaj.image.FImage;
import org.openimaj.image.MBFImage;
import org.openimaj.image.analyser.ImageAnalyser;
import org.openimaj.image.colour.Transforms;
import org.openimaj.image.mask.AbstractMaskedObject;

/**
 * A two-valued summary representing mean hue (in radians) and variance of hue
 * respectively. Additionally, can produce a classification for black & white
 * versus colour versus sepia images based on hand-coded (and not well tested)
 * parameters.
 * 
 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
 * 
 */
public class HueStats extends AbstractMaskedObject<FImage>
                implements
                        ImageAnalyser<MBFImage>,
                        FeatureVectorProvider<DoubleFV>
{
        double mean_x = 0;
        double m2_x = 0;
        double mean_y = 0;
        double m2_y = 0;
        int n = 0;

        /**
         * Construct with no mask set
         */
        public HueStats() {
                super();
        }

        /**
         * Construct with a mask.
         * 
         * @param mask
         *            the mask.
         */
        public HueStats(FImage mask) {
                super(mask);
        }

        @Override
        public void analyseImage(MBFImage image) {
                // reset vars in case we're reused
                mean_x = 0;
                m2_x = 0;
                mean_y = 0;
                m2_y = 0;
                n = 0;

                final FImage hue = Transforms.calculateHue(image);

                for (int j = 0; j < hue.height; j++) {
                        for (int i = 0; i < hue.width; i++) {
                                if (mask != null && mask.pixels[j][i] == 0)
                                        continue;

                                final double angle = hue.pixels[j][i];

                                final double x = Math.cos(2 * Math.PI * angle);
                                final double y = Math.sin(2 * Math.PI * angle);

                                n++;
                                final double delta_x = x - mean_x;
                                final double delta_y = y - mean_y;
                                mean_x += delta_x / n;
                                mean_y += delta_y / n;

                                m2_x += delta_x * (x - mean_x);
                                m2_y += delta_y * (y - mean_y);
                        }
                }
        }

        /**
         * Get the mean hue value.
         * 
         * @return the mean hue value over all pixels.
         */
        public double getMeanHue() {
                return Math.atan2(mean_y, mean_x);
        }

        /**
         * Get the variance in hue value.
         * 
         * @return the variance of hue over all pixels.
         */
        public double getHueVariance() {
                final double var_x = m2_x / n;
                final double var_y = m2_y / n;

                return var_y * var_x;
        }

        /**
         * Tonal attributes for images based on the mean hue and variance.
         * 
         * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
         * 
         */
        public enum ToneAttr {
                /**
                 * Sepia toned image.
                 */
                SEPIA,
                /**
                 * Black and white image.
                 */
                BLACK_AND_WHITE,
                /**
                 * Colour image
                 */
                COLOR;

                /**
                 * Estimate the tone from the given mean and variance of the hue. This
                 * is hand-crafted and not well tested. A variance bigger than 5e-4 is
                 * taken to imply a colour image. If the variance is less than 5e-4 and
                 * the mean hue is between -0.1 and 0.1 radians, then it is assumed the
                 * image is back and white. If the variance is less than 5e-4 and the
                 * mean hue is between -0.6 and 0.8 radians, then it is assumed the
                 * image is sepia toned.
                 * 
                 * @param mean
                 *            the mean hue
                 * @param var
                 *            the variance in hue
                 * @return the estimated tone
                 */
                public static ToneAttr getAttr(double mean, double var) {
                        if (var < 5e-4) {
                                if (mean > -0.1 && mean < 0.1)
                                        return BLACK_AND_WHITE;
                                if (mean > 0.6 && mean < 0.8)
                                        return SEPIA;
                        }
                        return COLOR;
                }
        }

        /**
         * Estimate the tone of the image.
         * 
         * @see ToneAttr#getAttr(double, double)
         * 
         * @return the estimated tone
         */
        public ToneAttr getTone() {
                return ToneAttr.getAttr(getMeanHue(), getHueVariance());
        }

        @Override
        public DoubleFV getFeatureVector() {
                return new DoubleFV(new double[] { getMeanHue(), getHueVariance() });
        }
}