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/**
* 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.processing.convolution;
import static java.lang.Math.exp;
import org.openimaj.image.FImage;
import org.openimaj.math.util.FloatArrayStatsUtils;
/**
* Simple 2D Gaussian convolution. In most cases the {@link FGaussianConvolve}
* filter will do the same thing, but much much faster!
*
* @author Jonathon Hare ([email protected])
*
*/
public class Gaussian2D extends FConvolution {
/**
* Construct with given kernel size and variance.
*
* @param width
* kernel width
* @param height
* kernel height
* @param sigma
* variance
*/
public Gaussian2D(int width, int height, float sigma) {
super(createKernelImage(width, height, sigma));
}
/**
* Construct with given kernel size and variance.
*
* @param size
* kernel width/height
* @param sigma
* variance
*/
public Gaussian2D(int size, float sigma) {
super(createKernelImage(size, size, sigma));
}
/**
* Create a kernel image with given kernel size and variance.
*
* @param size
* image height/width.
* @param sigma
* variance.
* @return new kernel image.
*/
public static FImage createKernelImage(int size, float sigma) {
return createKernelImage(size, size, sigma);
}
/**
* Create a kernel image with given kernel size and variance.
*
* @param width
* image width.
* @param height
* image height.
* @param sigma
* variance.
* @return new kernel image.
*/
public static FImage createKernelImage(int width, int height, float sigma) {
final FImage f = new FImage(width, height);
final int hw = (width - 1) / 2;
final int hh = (height - 1) / 2;
final float sigmasq = sigma * sigma;
for (int y = -hh, j = 0; y <= hh; y++, j++) {
for (int x = -hw, i = 0; x <= hw; x++, i++) {
final int radsqrd = x * x + y * y;
f.pixels[j][i] = (float) exp(-radsqrd / (2 * sigmasq));
}
}
final float sum = FloatArrayStatsUtils.sum(f.pixels);
return f.divideInplace(sum);
}
}