boofcv.alg.filter.convolve.ConvolveNormalizedSparse Maven / Gradle / Ivy

/*
 * Copyright (c) 2011-2016, 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.alg.filter.convolve;

import boofcv.alg.filter.convolve.normalized.ConvolveNormalizedStandardSparse;
import boofcv.struct.convolve.Kernel1D_F32;
import boofcv.struct.convolve.Kernel1D_I32;
import boofcv.struct.image.GrayF32;
import boofcv.struct.image.GrayS16;
import boofcv.struct.image.GrayU8;

/**
 * Performs a convolution around a single pixel only using two 1D kernels in the horizontal and vertical direction.
 * Borders are checked and if on an image border the kernel is truncated and re-normalized.  Only to be used with kernels
 * that can be re-normalized
 *
 * @author Peter Abeles
 */
public class ConvolveNormalizedSparse {

	/**
	 * Convolves around the specified point in the horizontal and vertical direction.  When at the border of
	 * the image the kernel is re-normalized.
	 *
	 * @param horizontal Kernel convolved across the point in the horizontal direction.
	 * @param vertical Kernel convolved across the point in the vertical direction.
	 * @param input Image being convolved.
	 * @param c_x The x-coordinate of the point being convolved.
	 * @param c_y The y-coordinate of the point being convolved.
	 * @param storage Temporary storage.  Needs to be the same size as the kernels being convolved.
	 * @return Result of the convolution.
	 */
	public static float convolve(Kernel1D_F32 horizontal, Kernel1D_F32 vertical,
								 GrayF32 input, int c_x , int c_y, float storage[] )
	{
		if( horizontal.width != vertical.width )
			throw new IllegalArgumentException("Both kernels need to be the same width.  Change code if this is a problem.");

		return ConvolveNormalizedStandardSparse.convolve(horizontal,vertical,input,c_x,c_y,storage);
	}

	/**
	 * Convolves around the specified point in the horizontal and vertical direction.  When at the border of
	 * the image the kernel is re-normalized.
	 *
	 * @param horizontal Kernel convolved across the point in the horizontal direction.
	 * @param vertical Kernel convolved across the point in the vertical direction.
	 * @param input Image being convolved.
	 * @param c_x The x-coordinate of the point being convolved.
	 * @param c_y The y-coordinate of the point being convolved.
	 * @param storage Temporary storage.  Needs to be the same size as the kernels being convolved.
	 * @return Result of the convolution.
	 */
	public static int convolve(Kernel1D_I32 horizontal, Kernel1D_I32 vertical,
							   GrayU8 input, int c_x , int c_y, int storage[] )
	{
		if( horizontal.width != vertical.width )
			throw new IllegalArgumentException("Both kernels need to be the same width.  Change code if this is a problem.");

		return ConvolveNormalizedStandardSparse.convolve(horizontal,vertical,input,c_x,c_y,storage);
	}

	/**
	 * Convolves around the specified point in the horizontal and vertical direction.  When at the border of
	 * the image the kernel is re-normalized.
	 *
	 * @param horizontal Kernel convolved across the point in the horizontal direction.
	 * @param vertical Kernel convolved across the point in the vertical direction.
	 * @param input Image being convolved.
	 * @param c_x The x-coordinate of the point being convolved.
	 * @param c_y The y-coordinate of the point being convolved.
	 * @param storage Temporary storage.  Needs to be the same size as the kernels being convolved.
	 * @return Result of the convolution.
	 */
	public static int convolve(Kernel1D_I32 horizontal, Kernel1D_I32 vertical,
							   GrayS16 input, int c_x , int c_y, int storage[] )
	{
		if( horizontal.width != vertical.width )
			throw new IllegalArgumentException("Both kernels need to be the same width.  Change code if this is a problem.");

		return ConvolveNormalizedStandardSparse.convolve(horizontal,vertical,input,c_x,c_y,storage);
	}
}