All Downloads are FREE. Search and download functionalities are using the official Maven repository.

boofcv.factory.transform.pyramid.FactoryPyramid Maven / Gradle / Ivy

Go to download

BoofCV is an open source Java library for real-time computer vision and robotics applications.

There is a newer version: 1.1.6
Show newest version
/*
 * 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);
	}
}




© 2015 - 2024 Weber Informatics LLC | Privacy Policy