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BoofCV is an open source Java library for real-time computer vision and robotics applications.
/*
* Copyright (c) 2011-2017, Peter Abeles. All Rights Reserved.
*
* This file is part of BoofCV (http://boofcv.org).
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package boofcv.factory.transform.pyramid;
import boofcv.alg.interpolate.InterpolatePixelS;
import boofcv.alg.transform.pyramid.PyramidDiscreteSampleBlur;
import boofcv.alg.transform.pyramid.PyramidFloatGaussianScale;
import boofcv.core.image.border.BorderType;
import boofcv.factory.filter.kernel.FactoryKernel;
import boofcv.factory.filter.kernel.FactoryKernelGaussian;
import boofcv.factory.interpolate.FactoryInterpolation;
import boofcv.struct.convolve.Kernel1D;
import boofcv.struct.image.ImageBase;
import boofcv.struct.image.ImageGray;
import boofcv.struct.image.ImageType;
import boofcv.struct.pyramid.PyramidDiscrete;
import boofcv.struct.pyramid.PyramidFloat;
/**
* Factory for creating classes related to image pyramids.
*
* @author Peter Abeles
*/
public class FactoryPyramid {
/**
* Creates an updater for discrete pyramids where a Gaussian is convolved across the input
* prior to sub-sampling.
*
* @param imageType Type of input image.
* @param sigma Gaussian sigma. If < 0 then a sigma is selected using the radius. Try -1.
* @param radius Radius of the Gaussian kernel. If < 0 then the radius is selected using sigma. Try 2.
* @return PyramidDiscrete
*/
public static >
PyramidDiscrete discreteGaussian( int[] scaleFactors , double sigma , int radius ,
boolean saveOriginalReference, ImageType imageType )
{
Class kernelType = FactoryKernel.getKernelType(imageType.getDataType(),1);
Kernel1D kernel = FactoryKernelGaussian.gaussian(kernelType,sigma,radius);
return new PyramidDiscreteSampleBlur<>(kernel, sigma, imageType, saveOriginalReference, scaleFactors);
}
/**
* Creates a float pyramid where each layer is blurred using a Gaussian with the specified
* sigma. Bilinear interpolation is used when sub-sampling.
*
* @param scaleFactors The scale factor of each layer relative to the previous layer.
* Layer 0 is relative to the input image.
* @param sigmas Gaussian blur magnitude for each layer.
* @param imageType Type of image in the pyramid.
* @return PyramidFloat
*/
public static >
PyramidFloat floatGaussian( double scaleFactors[], double []sigmas , Class imageType ) {
InterpolatePixelS interp = FactoryInterpolation.bilinearPixelS(imageType, BorderType.EXTENDED);
return new PyramidFloatGaussianScale<>(interp, scaleFactors, sigmas, imageType);
}
/**
* Constructs an image pyramid which is designed to mimic a {@link boofcv.struct.gss.GaussianScaleSpace}. Each layer in the pyramid
* should have the equivalent amount of blur that a space-space constructed with the same parameters would have.
*
* @param scaleSpace The scale of each layer and the desired amount of blur relative to the original image
* @param imageType Type of image
* @return PyramidFloat
*/
public static >
PyramidFloat scaleSpacePyramid( double scaleSpace[], Class imageType ) {
double[] sigmas = new double[ scaleSpace.length ];
sigmas[0] = scaleSpace[0];
for( int i = 1; i < scaleSpace.length; i++ ) {
// the desired amount of blur
double c = scaleSpace[i];
// the effective amount of blur applied to the last level
double b = scaleSpace[i-1];
// the amount of additional blur which is needed
sigmas[i] = Math.sqrt(c*c-b*b);
// take in account the change in image scale
sigmas[i] /= scaleSpace[i-1];
}
return floatGaussian(scaleSpace,sigmas,imageType);
}
/**
* Constructs a scale-space image pyramid. Each layer in the pyramid is the same size as the input image but
* has a different amount of blur applied to it.
*
* @param scaleSpace Amount of blur applied to each layer in the pyramid relative to the input image.
* @param imageType Type of image
* @param Type of image
* @return Scale-space image pyramid
*/
public static >
PyramidFloat scaleSpace( double scaleSpace[], Class imageType ) {
double[] scaleFactors = new double[ scaleSpace.length ];
for( int i = 0; i < scaleSpace.length; i++ ) {
scaleFactors[i] = 1;
}
// find the amount of blue that it needs to apply at each layer
double[] sigmas = new double[ scaleSpace.length ];
sigmas[0] = scaleSpace[0];
for( int i = 1; i < scaleSpace.length; i++ ) {
// the desired amount of blur
double c = scaleSpace[i];
// the effective amount of blur applied to the last level
double b = scaleSpace[i-1];
// the amount of additional blur which is needed
sigmas[i] = Math.sqrt(c*c-b*b);
}
return floatGaussian(scaleFactors,sigmas,imageType);
}
}