Loading...
Searching...
No Matches
bilateral_upsampling.hpp
/*
* Software License Agreement (BSD License)
*
* Point Cloud Library (PCL) - www.pointclouds.org
* Copyright (c) 2009-2012, 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 Willow Garage, Inc. 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.
*
*/
#ifndef PCL_SURFACE_IMPL_BILATERAL_UPSAMPLING_H_
#define PCL_SURFACE_IMPL_BILATERAL_UPSAMPLING_H_
#include <pcl/surface/bilateral_upsampling.h>
#include <algorithm>
#include <pcl/console/print.h>
#include <Eigen/LU> // for inverse
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointOutT> void
pcl::BilateralUpsampling<PointInT, PointOutT>::process (pcl::PointCloud<PointOutT> &output)
{
// Copy the header
output.header = input_->header;
if (!initCompute ())
{
output.width = output.height = 0;
output.clear ();
return;
}
if (input_->isOrganized () == false)
{
PCL_ERROR ("Input cloud is not organized.\n");
return;
}
// Invert projection matrix
unprojection_matrix_ = projection_matrix_.inverse ();
for (int i = 0; i < 3; ++i)
{
for (int j = 0; j < 3; ++j)
printf ("%f ", unprojection_matrix_(i, j));
printf ("\n");
}
// Perform the actual surface reconstruction
performProcessing (output);
deinitCompute ();
}
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointOutT> void
pcl::BilateralUpsampling<PointInT, PointOutT>::performProcessing (PointCloudOut &output)
{
output.resize (input_->size ());
float nan = std::numeric_limits<float>::quiet_NaN ();
Eigen::MatrixXf val_exp_depth_matrix;
Eigen::VectorXf val_exp_rgb_vector;
computeDistances (val_exp_depth_matrix, val_exp_rgb_vector);
for (int x = 0; x < static_cast<int> (input_->width); ++x)
for (int y = 0; y < static_cast<int> (input_->height); ++y)
{
int start_window_x = std::max (x - window_size_, 0),
start_window_y = std::max (y - window_size_, 0),
end_window_x = std::min (x + window_size_, static_cast<int> (input_->width)),
end_window_y = std::min (y + window_size_, static_cast<int> (input_->height));
float sum = 0.0f,
norm_sum = 0.0f;
for (int x_w = start_window_x; x_w < end_window_x; ++ x_w)
for (int y_w = start_window_y; y_w < end_window_y; ++ y_w)
{
float val_exp_depth = val_exp_depth_matrix (static_cast<Eigen::MatrixXf::Index> (x - x_w + window_size_),
static_cast<Eigen::MatrixXf::Index> (y - y_w + window_size_));
auto d_color = static_cast<Eigen::VectorXf::Index> (
std::abs ((*input_)[y_w * input_->width + x_w].r - (*input_)[y * input_->width + x].r) +
std::abs ((*input_)[y_w * input_->width + x_w].g - (*input_)[y * input_->width + x].g) +
std::abs ((*input_)[y_w * input_->width + x_w].b - (*input_)[y * input_->width + x].b));
float val_exp_rgb = val_exp_rgb_vector (d_color);
if (std::isfinite ((*input_)[y_w*input_->width + x_w].z))
{
sum += val_exp_depth * val_exp_rgb * (*input_)[y_w*input_->width + x_w].z;
norm_sum += val_exp_depth * val_exp_rgb;
}
}
output[y*input_->width + x].r = (*input_)[y*input_->width + x].r;
output[y*input_->width + x].g = (*input_)[y*input_->width + x].g;
output[y*input_->width + x].b = (*input_)[y*input_->width + x].b;
if (norm_sum != 0.0f)
{
float depth = sum / norm_sum;
Eigen::Vector3f pc (static_cast<float> (x) * depth, static_cast<float> (y) * depth, depth);
Eigen::Vector3f pw (unprojection_matrix_ * pc);
output[y*input_->width + x].x = pw[0];
output[y*input_->width + x].y = pw[1];
output[y*input_->width + x].z = pw[2];
}
else
{
output[y*input_->width + x].x = nan;
output[y*input_->width + x].y = nan;
output[y*input_->width + x].z = nan;
}
}
output.header = input_->header;
output.width = input_->width;
output.height = input_->height;
}
template <typename PointInT, typename PointOutT> void
pcl::BilateralUpsampling<PointInT, PointOutT>::computeDistances (Eigen::MatrixXf &val_exp_depth, Eigen::VectorXf &val_exp_rgb)
{
val_exp_depth.resize (2*window_size_+1,2*window_size_+1);
val_exp_rgb.resize (3*255+1);
int j = 0;
for (int dx = -window_size_; dx < window_size_+1; ++dx)
{
int i = 0;
for (int dy = -window_size_; dy < window_size_+1; ++dy)
{
float val_exp = std::exp (- (dx*dx + dy*dy) / (2.0f * static_cast<float> (sigma_depth_ * sigma_depth_)));
val_exp_depth(i,j) = val_exp;
i++;
}
j++;
}
for (int d_color = 0; d_color < 3*255+1; d_color++)
{
float val_exp = std::exp (- d_color * d_color / (2.0f * sigma_color_ * sigma_color_));
val_exp_rgb(d_color) = val_exp;
}
}
#define PCL_INSTANTIATE_BilateralUpsampling(T,OutT) template class PCL_EXPORTS pcl::BilateralUpsampling<T,OutT>;
#endif /* PCL_SURFACE_IMPL_BILATERAL_UPSAMPLING_H_ */
pcl::BilateralUpsampling::computeDistances
void computeDistances(Eigen::MatrixXf &val_exp_depth, Eigen::VectorXf &val_exp_rgb)
Computes the distance for depth and RGB.
Definition bilateral_upsampling.hpp:156
pcl::BilateralUpsampling::process
void process(pcl::PointCloud< PointOutT > &output) override
Method that does the actual processing on the input cloud.
Definition bilateral_upsampling.hpp:50
pcl::BilateralUpsampling::performProcessing
void performProcessing(pcl::PointCloud< PointOutT > &output) override
Abstract cloud processing method.
Definition bilateral_upsampling.hpp:88
pcl::PointCloud
PointCloud represents the base class in PCL for storing collections of 3D points.
Definition point_cloud.h:173
pcl::PointCloud::resize
void resize(std::size_t count)
Resizes the container to contain count elements.
Definition point_cloud.h:462
pcl::PointCloud::width
std::uint32_t width
The point cloud width (if organized as an image-structure).
Definition point_cloud.h:398
pcl::PointCloud::header
pcl::PCLHeader header
The point cloud header.
Definition point_cloud.h:392
pcl::PointCloud::height
std::uint32_t height
The point cloud height (if organized as an image-structure).
Definition point_cloud.h:400
pcl::PointCloud::clear
void clear()
Removes all points in a cloud and sets the width and height to 0.
Definition point_cloud.h:885