fast_bilateral.hpp
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#ifndef PCL_FILTERS_IMPL_FAST_BILATERAL_HPP_
#define PCL_FILTERS_IMPL_FAST_BILATERAL_HPP_
#include <pcl/common/io.h>
namespace pcl
{
template <typename PointT> void
FastBilateralFilter<PointT>::applyFilter (PointCloud &output)
{
if (!input_->isOrganized ())
{
PCL_ERROR ("[pcl::FastBilateralFilter] Input cloud needs to be organized.\n");
return;
}
copyPointCloud (*input_, output);
float base_max = -std::numeric_limits<float>::max (),
base_min = std::numeric_limits<float>::max ();
bool found_finite = false;
for (const auto& pt: output)
{
if (std::isfinite(pt.z))
{
base_max = std::max<float>(pt.z, base_max);
base_min = std::min<float>(pt.z, base_min);
found_finite = true;
}
}
if (!found_finite)
{
PCL_WARN ("[pcl::FastBilateralFilter] Given an empty cloud. Doing nothing.\n");
return;
}
for (auto& pt: output)
{
if (!std::isfinite(pt.z))
{
pt.z = base_max;
}
}
const float base_delta = base_max - base_min;
const std::size_t padding_xy = 2;
const std::size_t padding_z = 2;
const std::size_t small_width = static_cast<std::size_t> (static_cast<float> (input_->width - 1) / sigma_s_) + 1 + 2 * padding_xy;
const std::size_t small_height = static_cast<std::size_t> (static_cast<float> (input_->height - 1) / sigma_s_) + 1 + 2 * padding_xy;
const std::size_t small_depth = static_cast<std::size_t> (base_delta / sigma_r_) + 1 + 2 * padding_z;
Array3D data (small_width, small_height, small_depth);
for (std::size_t x = 0; x < input_->width; ++x)
{
const std::size_t small_x = static_cast<std::size_t> (static_cast<float> (x) / sigma_s_ + 0.5f) + padding_xy;
for (std::size_t y = 0; y < input_->height; ++y)
{
const float z = output (x,y).z - base_min;
const std::size_t small_y = static_cast<std::size_t> (static_cast<float> (y) / sigma_s_ + 0.5f) + padding_xy;
const std::size_t small_z = static_cast<std::size_t> (static_cast<float> (z) / sigma_r_ + 0.5f) + padding_z;
Eigen::Vector2f& d = data (small_x, small_y, small_z);
d[0] += output (x,y).z;
d[1] += 1.0f;
}
}
std::vector<long int> offset (3);
offset[0] = &(data (1,0,0)) - &(data (0,0,0));
offset[1] = &(data (0,1,0)) - &(data (0,0,0));
offset[2] = &(data (0,0,1)) - &(data (0,0,0));
Array3D buffer (small_width, small_height, small_depth);
for (std::size_t dim = 0; dim < 3; ++dim)
{
const long int off = offset[dim];
for (std::size_t n_iter = 0; n_iter < 2; ++n_iter)
{
std::swap (buffer, data);
for(std::size_t x = 1; x < small_width - 1; ++x)
for(std::size_t y = 1; y < small_height - 1; ++y)
{
Eigen::Vector2f* d_ptr = &(data (x,y,1));
Eigen::Vector2f* b_ptr = &(buffer (x,y,1));
for(std::size_t z = 1; z < small_depth - 1; ++z, ++d_ptr, ++b_ptr)
*d_ptr = (*(b_ptr - off) + *(b_ptr + off) + 2.0 * (*b_ptr)) / 4.0;
}
}
}
if (early_division_)
{
for (std::vector<Eigen::Vector2f, Eigen::aligned_allocator<Eigen::Vector2f> >::iterator d = data.begin (); d != data.end (); ++d)
*d /= ((*d)[0] != 0) ? (*d)[1] : 1;
for (std::size_t x = 0; x < input_->width; x++)
for (std::size_t y = 0; y < input_->height; y++)
{
const float z = output (x,y).z - base_min;
const Eigen::Vector2f D = data.trilinear_interpolation (static_cast<float> (x) / sigma_s_ + padding_xy,
static_cast<float> (y) / sigma_s_ + padding_xy,
z / sigma_r_ + padding_z);
output(x,y).z = D[0];
}
}
else
{
for (std::size_t x = 0; x < input_->width; ++x)
for (std::size_t y = 0; y < input_->height; ++y)
{
const float z = output (x,y).z - base_min;
const Eigen::Vector2f D = data.trilinear_interpolation (static_cast<float> (x) / sigma_s_ + padding_xy,
static_cast<float> (y) / sigma_s_ + padding_xy,
z / sigma_r_ + padding_z);
output (x,y).z = D[0] / D[1];
}
}
}
template <typename PointT> std::size_t
FastBilateralFilter<PointT>::Array3D::clamp (const std::size_t min_value,
const std::size_t max_value,
const std::size_t x)
{
if (x >= min_value && x <= max_value)
{
return x;
}
if (x < min_value)
{
return (min_value);
}
return (max_value);
}
template <typename PointT> Eigen::Vector2f
FastBilateralFilter<PointT>::Array3D::trilinear_interpolation (const float x,
const float y,
const float z)
{
const std::size_t x_index = clamp (0, x_dim_ - 1, static_cast<std::size_t> (x));
const std::size_t xx_index = clamp (0, x_dim_ - 1, x_index + 1);
const std::size_t y_index = clamp (0, y_dim_ - 1, static_cast<std::size_t> (y));
const std::size_t yy_index = clamp (0, y_dim_ - 1, y_index + 1);
const std::size_t z_index = clamp (0, z_dim_ - 1, static_cast<std::size_t> (z));
const std::size_t zz_index = clamp (0, z_dim_ - 1, z_index + 1);
const float x_alpha = x - static_cast<float> (x_index);
const float y_alpha = y - static_cast<float> (y_index);
const float z_alpha = z - static_cast<float> (z_index);
return
(1.0f-x_alpha) * (1.0f-y_alpha) * (1.0f-z_alpha) * (*this)(x_index, y_index, z_index) +
x_alpha * (1.0f-y_alpha) * (1.0f-z_alpha) * (*this)(xx_index, y_index, z_index) +
(1.0f-x_alpha) * y_alpha * (1.0f-z_alpha) * (*this)(x_index, yy_index, z_index) +
x_alpha * y_alpha * (1.0f-z_alpha) * (*this)(xx_index, yy_index, z_index) +
(1.0f-x_alpha) * (1.0f-y_alpha) * z_alpha * (*this)(x_index, y_index, zz_index) +
x_alpha * (1.0f-y_alpha) * z_alpha * (*this)(xx_index, y_index, zz_index) +
(1.0f-x_alpha) * y_alpha * z_alpha * (*this)(x_index, yy_index, zz_index) +
x_alpha * y_alpha * z_alpha * (*this)(xx_index, yy_index, zz_index);
}
} // namespace pcl
#endif /* PCL_FILTERS_IMPL_FAST_BILATERAL_HPP_ */
pcl::FastBilateralFilter::Array3D
Definition: fast_bilateral.h:116
pcl::FastBilateralFilter::Array3D::clamp
static std::size_t clamp(const std::size_t min_value, const std::size_t max_value, const std::size_t x)
Definition: fast_bilateral.hpp:170
pcl::FastBilateralFilter::Array3D::end
std::vector< Eigen::Vector2f, Eigen::aligned_allocator< Eigen::Vector2f > >::iterator end()
Definition: fast_bilateral.h:170
pcl::FastBilateralFilter::Array3D::trilinear_interpolation
Eigen::Vector2f trilinear_interpolation(const float x, const float y, const float z)
Definition: fast_bilateral.hpp:187
pcl::FastBilateralFilter::Array3D::begin
std::vector< Eigen::Vector2f, Eigen::aligned_allocator< Eigen::Vector2f > >::iterator begin()
Definition: fast_bilateral.h:166
pcl::FastBilateralFilter::applyFilter
void applyFilter(PointCloud &output) override
Filter the input data and store the results into output.
Definition: fast_bilateral.hpp:51
pcl::PointCloud
PointCloud represents the base class in PCL for storing collections of 3D points.
Definition: point_cloud.h:173
pcl::copyPointCloud
void copyPointCloud(const pcl::PointCloud< PointInT > &cloud_in, pcl::PointCloud< PointOutT > &cloud_out)
Copy all the fields from a given point cloud into a new point cloud.
Definition: io.hpp:144
pcl
Definition: convolution.h:46