#include <gaussian.h>

Public Member Functions
void	compute (float sigma, Eigen::VectorXf &kernel, unsigned kernel_width=MAX_KERNEL_WIDTH) const
void	compute (float sigma, Eigen::VectorXf &kernel, Eigen::VectorXf &derivative, unsigned kernel_width=MAX_KERNEL_WIDTH) const
void	computeGradients (const pcl::PointCloud< float > &input, const Eigen::VectorXf &gaussian_kernel, const Eigen::VectorXf &gaussian_kernel_derivative, pcl::PointCloud< float > &grad_x, pcl::PointCloud< float > &grad_y) const
template<typename PointT >
void	computeGradients (const pcl::PointCloud< PointT > &input, boost::function< float(const PointT &p)> field_accessor, const Eigen::VectorXf &gaussian_kernel, const Eigen::VectorXf &gaussian_kernel_derivative, pcl::PointCloud< float > &grad_x, pcl::PointCloud< float > &grad_y) const
void	convolve (const pcl::PointCloud< float > &input, const Eigen::VectorXf &horiz_kernel, const Eigen::VectorXf &vert_kernel, pcl::PointCloud< float > &output) const
template<typename PointT >
void	convolve (const pcl::PointCloud< PointT > &input, boost::function< float(const PointT &p)> field_accessor, const Eigen::VectorXf &horiz_kernel, const Eigen::VectorXf &vert_kernel, pcl::PointCloud< float > &output) const
void	convolveCols (const pcl::PointCloud< float > &input, const Eigen::VectorXf &kernel, pcl::PointCloud< float > &output) const
template<typename PointT >
void	convolveCols (const pcl::PointCloud< PointT > &input, boost::function< float(const PointT &p)> field_accessor, const Eigen::VectorXf &kernel, pcl::PointCloud< float > &output) const
void	convolveRows (const pcl::PointCloud< float > &input, const Eigen::VectorXf &kernel, pcl::PointCloud< float > &output) const
template<typename PointT >
void	convolveRows (const pcl::PointCloud< PointT > &input, boost::function< float(const PointT &p)> field_accessor, const Eigen::VectorXf &kernel, pcl::PointCloud< float > &output) const
	GaussianKernel ()
void	smooth (const pcl::PointCloud< float > &input, const Eigen::VectorXf &gaussian_kernel, pcl::PointCloud< float > &output) const
template<typename PointT >
void	smooth (const pcl::PointCloud< PointT > &input, boost::function< float(const PointT &p)> field_accessor, const Eigen::VectorXf &gaussian_kernel, pcl::PointCloud< float > &output) const
Static Public Attributes
static const unsigned	MAX_KERNEL_WIDTH = 71

Detailed Description

Class GaussianKernel assembles all the method for computing, convolving, smoothing, gradients computing an image using a gaussian kernel. The image is stored in point cloud elements intensity member or rgb or...

Author:: Nizar Sallem

Definition at line 57 of file gaussian.h.

Constructor & Destructor Documentation

pcl::GaussianKernel::GaussianKernel ( ) [inline]

Definition at line 61 of file gaussian.h.

Member Function Documentation

void pcl::GaussianKernel::compute	(	float	sigma,
		Eigen::VectorXf &	kernel,
		unsigned	kernel_width = `MAX_KERNEL_WIDTH`
	)		const

Computes the gaussian kernel and dervative assiociated to sigma. The kernel and derivative width are adjusted according.

Parameters:

[in]	sigma
[out]	kernel	the computed gaussian kernel
[in]	kernel_width	the desired kernel width upper bond

Exceptions:

pcl::KernelWidthTooSmallException

Definition at line 41 of file gaussian.cpp.

void pcl::GaussianKernel::compute	(	float	sigma,
		Eigen::VectorXf &	kernel,
		Eigen::VectorXf &	derivative,
		unsigned	kernel_width = `MAX_KERNEL_WIDTH`
	)		const

Computes the gaussian kernel and dervative assiociated to sigma. The kernel and derivative width are adjusted according.

Parameters:

[in]	sigma
[out]	kernel	the computed gaussian kernel
[out]	derivative	the computed kernel derivative
[in]	kernel_width	the desired kernel width upper bond

Exceptions:

pcl::KernelWidthTooSmallException

Definition at line 76 of file gaussian.cpp.

void pcl::GaussianKernel::computeGradients	(	const pcl::PointCloud< float > &	input,
		const Eigen::VectorXf &	gaussian_kernel,
		const Eigen::VectorXf &	gaussian_kernel_derivative,
		pcl::PointCloud< float > &	grad_x,
		pcl::PointCloud< float > &	grad_y
	)		const `[inline]`

Computes float image gradients using a gaussian kernel and gaussian kernel derivative.

Parameters:

[in]	input	image to compute gardients for
[in]	gaussian_kernel	the gaussian kernel to be used
[in]	gaussian_kernel_derivative	the associated derivative
[out]	grad_x	gradient along X direction
[out]	grad_y	gradient along Y direction

Note:: if output doesn't fit in input i.e. output.rows () < input.rows () or output.cols () < input.cols () then output is resized to input sizes.

Definition at line 197 of file gaussian.h.

template<typename PointT >

void pcl::GaussianKernel::computeGradients	(	const pcl::PointCloud< PointT > &	input,
		boost::function< float(const PointT &p)>	field_accessor,
		const Eigen::VectorXf &	gaussian_kernel,
		const Eigen::VectorXf &	gaussian_kernel_derivative,
		pcl::PointCloud< float > &	grad_x,
		pcl::PointCloud< float > &	grad_y
	)		const `[inline]`

Computes float image gradients using a gaussian kernel and gaussian kernel derivative.

Parameters:

[in]	input	image to compute gardients for
[in]	field_accessor	a field accessor
[in]	gaussian_kernel	the gaussian kernel to be used
[in]	gaussian_kernel_derivative	the associated derivative
[out]	grad_x	gradient along X direction
[out]	grad_y	gradient along Y direction

Note:: if output doesn't fit in input i.e. output.rows () < input.rows () or output.cols () < input.cols () then output is resized to input sizes.

Definition at line 219 of file gaussian.h.

void pcl::GaussianKernel::convolve	(	const pcl::PointCloud< float > &	input,
		const Eigen::VectorXf &	horiz_kernel,
		const Eigen::VectorXf &	vert_kernel,
		pcl::PointCloud< float > &	output
	)		const `[inline]`

Convolve a float image in the 2 directions

Parameters:

[in]	horiz_kernel	kernel for convolving rows
[in]	vert_kernel	kernel for convolving columns
[in]	input	image to convolve
[out]	output	the convolved image

Note:: if output doesn't fit in input i.e. output.rows () < input.rows () or output.cols () < input.cols () then output is resized to input sizes.

Definition at line 151 of file gaussian.h.

template<typename PointT >

void pcl::GaussianKernel::convolve	(	const pcl::PointCloud< PointT > &	input,
		boost::function< float(const PointT &p)>	field_accessor,
		const Eigen::VectorXf &	horiz_kernel,
		const Eigen::VectorXf &	vert_kernel,
		pcl::PointCloud< float > &	output
	)		const `[inline]`

Convolve a float image in the 2 directions

Parameters:

[in]	input	image to convolve
[in]	field_accessor	a field accessor
[in]	horiz_kernel	kernel for convolving rows
[in]	vert_kernel	kernel for convolving columns
[out]	output	the convolved image

Note:: if output doesn't fit in input i.e. output.rows () < input.rows () or output.cols () < input.cols () then output is resized to input sizes.

Definition at line 173 of file gaussian.h.

void pcl::GaussianKernel::convolveCols	(	const pcl::PointCloud< float > &	input,
		const Eigen::VectorXf &	kernel,
		pcl::PointCloud< float > &	output
	)		const

Convolve a float image columns by a given kernel.

Parameters:

[in]	input	the image to convolve
[in]	kernel	convolution kernel
[out]	output	the convolved image

Note:: if output doesn't fit in input i.e. output.rows () < input.rows () or output.cols () < input.cols () then output is resized to input sizes.

Definition at line 179 of file gaussian.cpp.

template<typename PointT >

void pcl::GaussianKernel::convolveCols	(	const pcl::PointCloud< PointT > &	input,
		boost::function< float(const PointT &p)>	field_accessor,
		const Eigen::VectorXf &	kernel,
		pcl::PointCloud< float > &	output
	)		const

Convolve a float image columns by a given kernel.

Parameters:

[in]	input	the image to convolve
[in]	field_accessor	a field accessor
[in]	kernel	convolution kernel
[out]	output	the convolved image

Note:: if output doesn't fit in input i.e. output.rows () < input.rows () or output.cols () < input.cols () then output is resized to input sizes.

Definition at line 79 of file gaussian.hpp.

void pcl::GaussianKernel::convolveRows	(	const pcl::PointCloud< float > &	input,
		const Eigen::VectorXf &	kernel,
		pcl::PointCloud< float > &	output
	)		const

Convolve a float image rows by a given kernel.

Parameters:

[in]	kernel	convolution kernel
[in]	input	the image to convolve
[out]	output	the convolved image

Note:: if output doesn't fit in input i.e. output.rows () < input.rows () or output.cols () < input.cols () then output is resized to input sizes.

Definition at line 134 of file gaussian.cpp.

template<typename PointT >

void pcl::GaussianKernel::convolveRows	(	const pcl::PointCloud< PointT > &	input,
		boost::function< float(const PointT &p)>	field_accessor,
		const Eigen::VectorXf &	kernel,
		pcl::PointCloud< float > &	output
	)		const

Convolve a float image rows by a given kernel.

Parameters:

[in]	input	the image to convolve
[in]	field_accessor	a field accessor
[in]	kernel	convolution kernel
[out]	output	the convolved image

Note:: if output doesn't fit in input i.e. output.rows () < input.rows () or output.cols () < input.cols () then output is resized to input sizes.

Definition at line 46 of file gaussian.hpp.

void pcl::GaussianKernel::smooth	(	const pcl::PointCloud< float > &	input,
		const Eigen::VectorXf &	gaussian_kernel,
		pcl::PointCloud< float > &	output
	)		const `[inline]`

Smooth image using a gaussian kernel.

Parameters:

[in]	input	image
[in]	gaussian_kernel	the gaussian kernel to be used
[out]	output	the smoothed image

Note:: if output doesn't fit in input i.e. output.rows () < input.rows () or output.cols () < input.cols () then output is resized to input sizes.

Definition at line 238 of file gaussian.h.

template<typename PointT >

void pcl::GaussianKernel::smooth	(	const pcl::PointCloud< PointT > &	input,
		boost::function< float(const PointT &p)>	field_accessor,
		const Eigen::VectorXf &	gaussian_kernel,
		pcl::PointCloud< float > &	output
	)		const `[inline]`

Smooth image using a gaussian kernel.

Parameters:

[in]	input	image
[in]	field_accessor	a field accessor
[in]	gaussian_kernel	the gaussian kernel to be used
[out]	output	the smoothed image

Note:: if output doesn't fit in input i.e. output.rows () < input.rows () or output.cols () < input.cols () then output is resized to input sizes.

Definition at line 254 of file gaussian.h.

Member Data Documentation

const unsigned pcl::GaussianKernel::MAX_KERNEL_WIDTH = 71 [static]

Definition at line 63 of file gaussian.h.

The documentation for this class was generated from the following files:

Public Member Functions

Static Public Attributes

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation