org.openimaj.image.feature.global.Sharpness Maven / Gradle / Ivy
Go to download
Show more of this group Show more artifacts with this name
Show all versions of image-feature-extraction Show documentation
Show all versions of image-feature-extraction Show documentation
Methods for the extraction of low-level image features, including global image features and pixel/patch classification models.
/**
* 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.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.mask.AbstractMaskedObject;
import org.openimaj.image.processing.convolution.AverageBoxFilter;
import org.openimaj.image.processing.convolution.Laplacian3x3;
/**
* Sharpness measures the clarity and level of detail of an image. This class
* measures the Sharpness of an image as a function of its Laplacian, normalized
* by the local average luminance in the surroundings of each pixel.
*
* @author Jonathon Hare
*
*/
@Reference(
type = ReferenceType.Inproceedings,
author = { "Jose San Pedro", "Stefan Siersdorfer" },
title = "Ranking and Classifying Attractiveness of Photos in Folksonomies",
year = "2009",
booktitle = "18th International World Wide Web Conference",
pages = { "771", "", "771" },
url = "http://www2009.eprints.org/78/",
month = "April")
public class Sharpness extends AbstractMaskedObject
implements
ImageAnalyser,
FeatureVectorProvider
{
private final Laplacian3x3 laplacian = new Laplacian3x3();
private final AverageBoxFilter average = new AverageBoxFilter(3, 3);
protected double sharpness;
/**
* Construct with no mask set
*/
public Sharpness() {
super();
}
/**
* Construct with a mask.
*
* @param mask
* the mask.
*/
public Sharpness(FImage mask) {
super(mask);
}
@Override
public DoubleFV getFeatureVector() {
return new DoubleFV(new double[] { sharpness });
}
@Override
public void analyseImage(FImage image) {
final FImage limg = image.process(laplacian);
final FImage aimg = image.process(average);
double sum = 0;
for (int r = 0; r < limg.height; r++) {
for (int c = 0; c < limg.width; c++) {
if (mask != null && mask.pixels[r][c] == 0)
continue;
if (aimg.pixels[r][c] != 0) {
sum += Math.abs(limg.pixels[r][c] / aimg.pixels[r][c]);
}
}
}
sharpness = sum / (limg.height * limg.width);
}
/**
* Get the sharpness of the last image processed with
* {@link #analyseImage(FImage)}.
*
* @return the sharpness value
*/
public double getSharpness() {
return sharpness;
}
}
© 2015 - 2024 Weber Informatics LLC | Privacy Policy