/**
 * 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
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package org.openimaj.image.saliency;

import org.openimaj.citation.annotation.Reference;
import org.openimaj.citation.annotation.ReferenceType;
import org.openimaj.image.FImage;
import org.openimaj.image.analysis.algorithm.HorizontalProjection;
import org.openimaj.image.analysis.algorithm.VerticalProjection;
import org.openimaj.math.geometry.shape.Rectangle;

/**
 * Extract the subject region of an image based on the
 * part that is least blurred (most in-focus).
 * <p>
 * Algorithm based on:
 * Yiwen Luo and Xiaoou Tang. 2008. 
 * Photo and Video Quality Evaluation: Focusing on the Subject. 
 * In Proceedings of the 10th European Conference on Computer Vision: 
 * Part III (ECCV '08), David Forsyth, Philip Torr, and Andrew Zisserman (Eds.). 
 * Springer-Verlag, Berlin, Heidelberg, 386-399. DOI=10.1007/978-3-540-88690-7_29 
 * http://dx.doi.org/10.1007/978-3-540-88690-7_29
 * <p>
 * Note that this is not scale invariant - you will get different results with
 * different sized images...
 * 
 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
 */
@Reference(
                type = ReferenceType.Inproceedings,
                author = { "Luo, Yiwen", "Tang, Xiaoou" },
                title = "Photo and Video Quality Evaluation: Focusing on the Subject",
                year = "2008",
                booktitle = "Proceedings of the 10th European Conference on Computer Vision: Part III",
                pages = { "386", "", "399" },
                url = "http://dx.doi.org/10.1007/978-3-540-88690-7_29",
                publisher = "Springer-Verlag",
                series = "ECCV '08",
                customData = { 
                                "isbn", "978-3-540-88689-1", 
                                "location", "Marseille, France", 
                                "numpages", "14", 
                                "doi", "10.1007/978-3-540-88690-7_29", 
                                "acmid", "1478204", 
                                "address", "Berlin, Heidelberg" 
                }
        )
public class LuoTangSubjectRegion implements SaliencyMapGenerator<FImage> {
        DepthOfFieldEstimator dofEstimator;
        
        Rectangle roi;
        private FImage dofMap;
        private float alpha = 0.9f;
        
        /**
         * Construct with default values for the {@link DepthOfFieldEstimator} 
         * and an alpha parameter of 0.9.
         */
        public LuoTangSubjectRegion() {
                dofEstimator = new DepthOfFieldEstimator();
        }
        
        /**
         * Construct with the given parameters.
         * @param alpha the alpha value.
         * @param maxKernelSize Maximum kernel size for the {@link DepthOfFieldEstimator}.
         * @param kernelSizeStep Kernel step size for the {@link DepthOfFieldEstimator}.
         * @param nbins Number of bins for the {@link DepthOfFieldEstimator}.
         * @param windowSize window size for the {@link DepthOfFieldEstimator}.
         */
        public LuoTangSubjectRegion(float alpha, int maxKernelSize, int kernelSizeStep, int nbins, int windowSize) {
                this.dofEstimator = new DepthOfFieldEstimator(maxKernelSize, kernelSizeStep, nbins, windowSize);
                this.alpha = alpha;
        }
        
        /* (non-Javadoc)
         * @see org.openimaj.image.analyser.ImageAnalyser#analyseImage(org.openimaj.image.Image)
         */
        @Override
        public void analyseImage(FImage image) {
                image.analyseWith(dofEstimator);
                dofMap = dofEstimator.getSaliencyMap();
                
                for (int y=0; y<dofMap.height; y++) {
                        for (int x=0; x<dofMap.width; x++) {
                                if (dofMap.pixels[y][x] == 0) 
                                        dofMap.pixels[y][x] = 1;
                                else 
                                        dofMap.pixels[y][x] = 0;
                        }
                }
        }
        
        /**
         * @return the estimated rectangular region of interest
         */
        public Rectangle calculateROI() {               
                float [] pUx = HorizontalProjection.project(dofMap);
                float [] pUy = VerticalProjection.project(dofMap);
                
                float energy = 0;
                for (float f : pUx) energy += f;
                float thresh = energy * ((1 - alpha) / 2);
                
                int x1 = 0;
                float tmp = pUx[x1];
                while (tmp < thresh) {
                        x1++;
                        tmp += pUx[x1];
                }
                
                int y1 = 0;
                tmp = pUy[y1];
                while (tmp < thresh) {
                        y1++;
                        tmp += pUy[y1];
                }
                
                int x2 = pUx.length - 1;
                tmp = pUx[x2];
                while (tmp < thresh) {
                        x2--;
                        tmp += pUx[x2];
                }
                
                int y2 = pUy.length - 1;
                tmp = pUy[y2];
                while (tmp < thresh) {
                        y2--;
                        tmp += pUy[y2];
                }
                
                return new Rectangle(x1, y1, x2-x1, y2-y1);
        }

        @Override
        public FImage getSaliencyMap() {
                return dofMap;
        }
        
        /**
         * @return a mask image showing the region of interest.
         */
        public FImage getROIMap() {
                FImage image = new FImage(dofMap.width, dofMap.height);
                image.drawShapeFilled(calculateROI(), 1f);
                return image;
        }
}