/* * Software License Agreement (BSD License) * * Point Cloud Library (PCL) - www.pointclouds.org * Copyright (c) 2010-2011, Willow Garage, Inc. * * 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 copyright holder(s) 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. * * $Id$ * */ #pragma once #include #include namespace pcl { template void GaussianKernel::convolveRows(const pcl::PointCloud &input, std::function field_accessor, const Eigen::VectorXf& kernel, pcl::PointCloud &output) const { assert(kernel.size () % 2 == 1); int kernel_width = kernel.size () -1; int radius = kernel.size () / 2.0; if(output.height < input.height || output.width < input.width) { output.width = input.width; output.height = input.height; output.resize (input.height * input.width); } int i; for(int j = 0; j < input.height; j++) { for (i = 0 ; i < radius ; i++) output (i,j) = 0; for ( ; i < input.width - radius ; i++) { output (i,j) = 0; for (int k = kernel_width, l = i - radius; k >= 0 ; k--, l++) output (i,j) += field_accessor (input (l,j)) * kernel[k]; } for ( ; i < input.width ; i++) output (i,j) = 0; } } template void GaussianKernel::convolveCols(const pcl::PointCloud &input, std::function field_accessor, const Eigen::VectorXf& kernel, pcl::PointCloud &output) const { assert(kernel.size () % 2 == 1); int kernel_width = kernel.size () -1; int radius = kernel.size () / 2.0; if(output.height < input.height || output.width < input.width) { output.width = input.width; output.height = input.height; output.resize (input.height * input.width); } int j; for(int i = 0; i < input.width; i++) { for (j = 0 ; j < radius ; j++) output (i,j) = 0; for ( ; j < input.height - radius ; j++) { output (i,j) = 0; for (int k = kernel_width, l = j - radius ; k >= 0 ; k--, l++) { output (i,j) += field_accessor (input (i,l)) * kernel[k]; } } for ( ; j < input.height ; j++) output (i,j) = 0; } } } // namespace pcl