/**
    * 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 java.util.List;
  
  import org.openimaj.citation.annotation.Reference;
  import org.openimaj.citation.annotation.ReferenceType;
  import org.openimaj.feature.DoubleFV;
  import org.openimaj.feature.FeatureVectorProvider;
  import org.openimaj.image.MBFImage;
  import org.openimaj.image.analyser.ImageAnalyser;
  import org.openimaj.image.analysis.colour.CIEDE2000;
  import org.openimaj.image.colour.ColourSpace;
  import org.openimaj.image.pixel.ConnectedComponent;
  import org.openimaj.image.pixel.Pixel;
  import org.openimaj.image.pixel.PixelSet;
  import org.openimaj.image.segmentation.FelzenszwalbHuttenlocherSegmenter;
  
  /**
   * Implementation of a color contrast feature.
   * <p>
   * The feature is calculated by performing a weighted average of the average
   * colour difference of all the segments in the image.
   * 
   * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
   */
  @Reference(
  		type = ReferenceType.Inproceedings,
  		author = { "Che-Hua Yeh", "Yuan-Chen Ho", "Brian A. Barsky", "Ming Ouhyoung" },
  		title = "Personalized Photograph Ranking and Selection System",
  		year = "2010",
  		booktitle = "Proceedings of ACM Multimedia",
  		pages = { "211", "220" },
  		month = "October",
  		customData = { "location", "Florence, Italy" })
  public class ColourContrast implements ImageAnalyser<MBFImage>, FeatureVectorProvider<DoubleFV> {
  	FelzenszwalbHuttenlocherSegmenter<MBFImage> segmenter;
  	double contrast;
  
  	/**
  	 * Construct the {@link ColourContrast} feature extractor using the default
  	 * settings for the {@link FelzenszwalbHuttenlocherSegmenter}.
  	 */
  	public ColourContrast() {
  		segmenter = new FelzenszwalbHuttenlocherSegmenter<MBFImage>();
  	}
  
  	/**
  	 * Construct the {@link ColourContrast} feature extractor with the given
  	 * parameters for the underlying {@link FelzenszwalbHuttenlocherSegmenter}.
  	 * 
  	 * @param sigma
  	 *            amount of blurring
  	 * @param k
  	 *            threshold
  	 * @param minSize
  	 *            minimum allowed component size
  	 */
  	public ColourContrast(float sigma, float k, int minSize) {
  		segmenter = new FelzenszwalbHuttenlocherSegmenter<MBFImage>(sigma, k, minSize);
  	}
  
  	@Override
  	public DoubleFV getFeatureVector() {
  		return new DoubleFV(new double[] { contrast });
  	}
  
  	/*
  	 * (non-Javadoc)
  	 * 
  	 * @see
 	 * org.openimaj.image.processor.ImageProcessor#processImage(org.openimaj
 	 * .image.Image)
 	 */
 	@Override
 	public void analyseImage(MBFImage image) {
 		final List<ConnectedComponent> ccs = segmenter.segment(image);
 		final MBFImage labImage = ColourSpace.convert(image, ColourSpace.CIE_Lab);
 		final float[][] avgs = new float[ccs.size()][3];
 		final int w = image.getWidth();
 		final int h = image.getHeight();
 
 		// calculate patch average colours
 		for (int i = 0; i < avgs.length; i++) {
 			for (final Pixel p : ccs.get(i).pixels) {
 				final Float[] v = labImage.getPixel(p);
 
 				avgs[i][0] += v[0];
 				avgs[i][0] += v[1];
 				avgs[i][0] += v[2];
 			}
 			final int sz = ccs.get(i).pixels.size();
 			avgs[i][0] /= sz;
 			avgs[i][1] /= sz;
 			avgs[i][2] /= sz;
 		}
 
 		for (int i = 0; i < avgs.length; i++) {
 			for (int j = i + 1; j < avgs.length; j++) {
 				final PixelSet ci = ccs.get(i);
 				final PixelSet cj = ccs.get(i);
 				final float C = CIEDE2000.calculateDeltaE(avgs[i], avgs[j]);
 
 				contrast += (1 - distance(ci, cj, w, h)) * (C / (ci.calculateArea() * cj.calculateArea()));
 			}
 		}
 	}
 
 	float distance(PixelSet c1, PixelSet c2, int w, int h) {
 		final double[] cen1 = c1.calculateCentroid();
 		final double[] cen2 = c2.calculateCentroid();
 
 		final double dx = (cen1[0] - cen2[0]) / w;
 		final double dy = (cen1[1] - cen2[1]) / h;
 
 		return (float) (Math.sqrt(dx * dx + dy * dy) / Math.sqrt(2));
 	}
 }