/**
    * 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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   * (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.
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  package org.openimaj.image.feature.global;
  
  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.FImage;
  import org.openimaj.image.analyser.ImageAnalyser;
  import org.openimaj.image.processor.GridProcessor;
  import org.openimaj.math.util.FloatArrayStatsUtils;
  
  /**
   * Implementation of the Bokeh estimation feature described by Yeh et al.
   * 
   * @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 YehBokehEstimator implements ImageAnalyser<FImage>, FeatureVectorProvider<DoubleFV> {
  	class Sharpness implements GridProcessor<Float, FImage> {
  		SharpPixelProportion bpp = new SharpPixelProportion();
  
  		@Override
  		public int getHorizontalGridElements() {
  			return nBlocksX;
  		}
  
  		@Override
  		public int getVerticalGridElements() {
  			return nBlocksY;
  		}
  
  		@Override
  		public Float processGridElement(FImage patch) {
  			patch.analyseWith(bpp);
  			return (float) bpp.getBlurredPixelProportion();
  		}
  	}
  
  	class GreyLevelVariance implements GridProcessor<Float, FImage> {
  		@Override
  		public int getHorizontalGridElements() {
  			return nBlocksX;
  		}
  
  		@Override
  		public int getVerticalGridElements() {
  			return nBlocksY;
  		}
  
  		@Override
  		public Float processGridElement(FImage patch) {
  			return FloatArrayStatsUtils.var(patch.pixels);
  		}
  	}
  
  	Sharpness sharpProcessor = new Sharpness();
  	GreyLevelVariance varProcessor = new GreyLevelVariance();
  
  	int nBlocksX = 5;
  	int nBlocksY = 5;
  
 	float varThreshold = 0.1f;
 	float sharpnessThreshold = 0.5f;
 	float lowerBound = 0.3f;
 	float upperBound = 0.7f;
 
 	double bokeh;
 
 	/**
 	 * Construct with defaults: 5x5 blocks, variance threshold of 0.1, sharpness
 	 * threshold of 0.5, lower bound of 0.3, upper bound of 0.7
 	 */
 	public YehBokehEstimator() {
 	}
 
 	/**
 	 * Construct with the given parameters.
 	 * 
 	 * @param nBlocksX
 	 *            number of blocks in the x-direction
 	 * @param nBlocksY
 	 *            number of blocks in the y-direction
 	 * @param varThreshold
 	 *            threshold for the variance
 	 * @param sharpnessThreshold
 	 *            threshold for the sharpness
 	 * @param lowerBound
 	 *            lower bound on Qbokeh for bokeh to be detected
 	 * @param upperBound
 	 *            upper bound on Qbokeh for bokeh to be detected
 	 */
 	public YehBokehEstimator(int nBlocksX, int nBlocksY, float varThreshold, float sharpnessThreshold, float lowerBound,
 			float upperBound)
 	{
 		this.nBlocksX = nBlocksX;
 		this.nBlocksY = nBlocksY;
 		this.varThreshold = varThreshold;
 		this.sharpnessThreshold = sharpnessThreshold;
 		this.lowerBound = lowerBound;
 		this.upperBound = upperBound;
 	}
 
 	@Override
 	public DoubleFV getFeatureVector() {
 		return new DoubleFV(new double[] { bokeh });
 	}
 
 	/*
 	 * (non-Javadoc)
 	 * 
 	 * @see
 	 * org.openimaj.image.processor.ImageProcessor#processImage(org.openimaj
 	 * .image.Image)
 	 */
 	@Override
 	public void analyseImage(FImage image) {
 		final FImage sharpness = image.process(sharpProcessor);
 		final FImage variance = image.process(varProcessor);
 
 		double Qbokeh = 0;
 		int validBlocks = 0;
 		for (int y = 0; y < sharpness.height; y++) {
 			for (int x = 0; x < sharpness.width; x++) {
 				if (variance.pixels[y][x] >= varThreshold) {
 					Qbokeh += sharpness.pixels[y][x] > 0.5 ? 1 : 0;
 					validBlocks++;
 				}
 			}
 		}
 		Qbokeh /= (validBlocks);
 
 		bokeh = (Qbokeh >= lowerBound && Qbokeh <= upperBound) ? 1 : 0;
 	}
 }