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.saliency; 031 032import org.openimaj.citation.annotation.Reference; 033import org.openimaj.citation.annotation.ReferenceType; 034import org.openimaj.image.FImage; 035import org.openimaj.image.MBFImage; 036import org.openimaj.image.colour.ColourSpace; 037import org.openimaj.image.processing.convolution.FGaussianConvolve; 038 039/** 040 * Implementation of the saliency map algorithm described in: 041 * 042 * R. Achanta, S. Hemami, F. Estrada and S. Susstrunk, Frequency-tuned Salient 043 * Region Detection, IEEE International Conference on Computer Vision and 044 * Pattern Recognition (CVPR), 2009. 045 * 046 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk) 047 */ 048@Reference( 049 type = ReferenceType.Inproceedings, 050 author = { "Achanta, Radhakrishna", "Hemami, Sheila", "Estrada, Francisco", "S{\"u}sstrunk, Sabine" }, 051 title = "Frequency-tuned {S}alient {R}egion {D}etection", 052 year = "2009", 053 booktitle = "{IEEE} {I}nternational {C}onference on {C}omputer {V}ision and {P}attern {R}ecognition ({CVPR})", 054 url = "http://infoscience.epfl.ch/record/135217/files/1708.pdf", 055 customData = { "Affiliation", "EPFL", "Details", "http://infoscience.epfl.ch/record/135217", "Keywords", "IVRG; NCCR-MICS; NCCR-MICS/CL4; K-Space; PHAROS; Saliency; Segmentation; Frequency-domain analysis", "Location", "Miami Beach, Florida" } 056 ) 057public class AchantaSaliency implements SaliencyMapGenerator<MBFImage> { 058 protected float sigma; 059 protected FImage map; 060 061 /** 062 * Construct with the given amount of smoothing. 063 * @param sigma standard deviation of Gaussian kernel smoothing 064 */ 065 public AchantaSaliency(float sigma) { 066 this.sigma = sigma; 067 } 068 069 /** 070 * Construct with a smoothing of 1 pixel standard deviation. 071 */ 072 public AchantaSaliency() { 073 this.sigma = 1; 074 } 075 076 /* (non-Javadoc) 077 * @see org.openimaj.image.analyser.ImageAnalyser#analyseImage(org.openimaj.image.Image) 078 */ 079 @Override 080 public void analyseImage(MBFImage image) { 081 int width = image.getWidth(); 082 int height = image.getHeight(); 083 084 MBFImage lab = ColourSpace.convert(image, ColourSpace.CIE_Lab); 085 086 float[][] Lb = lab.getBand(0).pixels; 087 float[][] ab = lab.getBand(1).pixels; 088 float[][] bb = lab.getBand(2).pixels; 089 float mL = 0, ma = 0, mb = 0; 090 091 for (int y=0; y<height; y++) { 092 for (int x=0; x<width; x++) { 093 mL += Lb[y][x]; 094 ma += ab[y][x]; 095 mb += bb[y][x]; 096 } 097 } 098 099 mL /= (height*width); 100 ma /= (height*width); 101 mb /= (height*width); 102 103 //blur 104 MBFImage blur = lab.process(new FGaussianConvolve(sigma)); 105 Lb = blur.getBand(0).pixels; 106 ab = blur.getBand(1).pixels; 107 bb = blur.getBand(2).pixels; 108 109 //create map 110 map = new FImage(width, height); 111 for (int y=0; y<height; y++) { 112 for (int x=0; x<width; x++) { 113 float dL = (Lb[y][x]-mL); 114 float da = (ab[y][x]-ma); 115 float db = (bb[y][x]-mb); 116 117 map.pixels[y][x] = dL*dL + da*da + db*db; 118 } 119 } 120 map.normalise(); 121 } 122 123 @Override 124 public FImage getSaliencyMap() { 125 return map; 126 } 127}