Functions
template<class D >
Image< D >	AdaptiveAnisotropicDiffusion (Image< D > img, const DiffusionFunction *diff_func, float init_kappa, float radius=1.0)
	Computes and returns a filtered image by anisotropic diffusion. More...

template<class D >
Image< D >	AnisotropicDiffusion (Image< D > img, const DiffusionFunction *diff_func, float kappa, size_t iterations, float radius=1.0)
	Computes and returns a filtered image by anisotropic diffusion. More...

template<class D >
void	AnisotropicDiffusionThread (Image< D > &img, Image< D > &res, double integration_constant, const DiffusionFunction *diff_func, float kappa, Adjacency &adj, size_t thread, size_t total_threads)
	Threads implementation for anisotropic diffusion filter. More...

template<class D >
double	Flow (const Image< D > &img, const DiffusionFunction *diff_func, float kappa, const size_t pxl, const Adjacency &adj)
	The flow is computed based the diffusion function. More...

template<class D >
Image< D >	Gaussian (const Image< D > &img, float radius=2.0, float std_dev=2.0)
	Returns the median filtered image with the given radius. More...

template<class D >
Image< D >	Mean (const Image< D > &img, float radius)
	Returns the mean filtered image with the given radius. More...

template<class D >
Image< D >	Mean (const Image< D > &img, const Image< D > &msk, float radius)
	Returns the mean filtered image with the given radius restricted to non-zero mask pixels. More...

template<class D >
Image< D >	Median (const Image< D > &img, float radius)
	Returns the median filtered image with the given radius. More...

template<class D >
void	MedianThreads (const Image< D > &img, const Adjacency &adj, Image< D > &res, size_t thread, size_t total_threads)
	Multi-thread implementation of the median filtered image with the given radius. More...

template<class D >
float	EdgeRegionKappa (const Image< D > &source, const Image< D > &mask, const DiffusionFunction *diff_func, float radius)
	Finds the best edge kappa to filter source image. More...

template<class D >
float	FlatRegionKappa (const Image< D > &source, const Image< D > &mask, const DiffusionFunction *diff_func, float radius, float kappa)
	Finds the best flat kappa to filter source image. More...

template<class D >
Image< D >	OptimalAnisotropicDiffusion (Image< D > img, const DiffusionFunction *diff_func, float radius, float conservativeness)
	Threads implementation for anisotropic diffusion filter. More...

template<class D >
Image< D >	OptimalAnisotropicDiffusion (Image< D > img, const DiffusionFunction *diff_func, float radius, float conservativeness, const Image< D > &canny, const Image< D > &backg)
	Threads implementation for anisotropic diffusion filter. More...

Function Documentation

template<class D >

Image< D > Bial::Filtering::AdaptiveAnisotropicDiffusion	(	Image< D >	img,
		const DiffusionFunction *	diff_func,
		float	init_kappa,
		float	radius = `1.0`
	)

Computes and returns a filtered image by anisotropic diffusion.

Date: 2013/Nov/18

Parameters

img	Input image.
diff_function	diffusion function.
init_kappa	initial kappa constant to control the gradient range to be filtered.
radius	radius of the adjacency relation.

Returns: Returns filtered image by anisotropic diffusion.

Warning: none.

template<class D >

Image< D > Bial::Filtering::AnisotropicDiffusion	(	Image< D >	img,
		const DiffusionFunction *	diff_func,
		float	kappa,
		size_t	iterations,
		float	radius = `1.0`
	)

Computes and returns a filtered image by anisotropic diffusion.

Date: 2013/Nov/18

Parameters

img	Input image.
diff_function	diffusion function.
kappa	constant to control the gradient range to be filtered.
iterations	the number of iterations.
radius	radius of the adjacency relation.

Returns: Returns filtered image by anisotropic diffusion.

Warning: none.

template<class D >

void Bial::Filtering::AnisotropicDiffusionThread	(	Image< D > &	img,
		Image< D > &	res,
		double	integration_constant,
		const DiffusionFunction *	diff_func,
		float	kappa,
		Adjacency &	adj,
		size_t	thread,
		size_t	total_threads
	)

Threads implementation for anisotropic diffusion filter.

Date: 2013/Nov/27

Parameters

img	Input image.
res	Output image.
integration_constant	Constant of integration based on adjacency size.
diff_function	diffusion function.
kappa	constant to control the gradient range to be filtered.
adj	An adjacency relation.
thread	Thread number.
total_threads	Number of threads.

Returns: none.

Warning: none.

template<class D >

float Bial::Filtering::EdgeRegionKappa	(	const Image< D > &	source,
		const Image< D > &	mask,
		const DiffusionFunction *	diff_func,
		float	radius
	)

Finds the best edge kappa to filter source image.

Date: 2013/Nov/29

Parameters

source	Input image.
mask	Input mask with edge region.
diff_function	diffusion function.
radius	Adjacency radius for diff_function.

Returns: Best edge kappa to filter source image.

Warning: none.

template<class D >

float Bial::Filtering::FlatRegionKappa	(	const Image< D > &	source,
		const Image< D > &	mask,
		const DiffusionFunction *	diff_func,
		float	radius,
		float	kappa
	)

Finds the best flat kappa to filter source image.

Date: 2013/Nov/29

Parameters

source	Input image.
mask	Input mask with edge region.
diff_function	diffusion function.
radius	Adjacency radius for diff_function.
kappa	Best edge kappa used for initialization.

Returns: Best flat kappa to filter source image.

Warning: none.

template<class D >

double Bial::Filtering::Flow	(	const Image< D > &	img,
		const DiffusionFunction *	diff_func,
		float	kappa,
		const size_t	pxl,
		const Adjacency &	adj
	)

The flow is computed based the diffusion function.

Date: 2013/Nov/18

Parameters

img	Input image.
diff_function	diffusion function.
kappa	constant to control the gradient range to be filtered.
pxl	reference pixel.
adj	adjacency relation.

Returns: Returns the value of the flow of pxl with respect to its adjacents in adjacency adj.

Warning: none.

template<class D >

Image< D > Bial::Filtering::Gaussian	(	const Image< D > &	img,
		float	radius = `2.0`,
		float	std_dev = `2.0`
	)

Returns the median filtered image with the given radius.

Date: 2013/Nov/22

Parameters

img	Input image.
neighborhood_radius	radius of the neighborhood.

Returns: Median filtered image with the given radius.

Warning: none.

template<class D >

Image< D > Bial::Filtering::Mean	(	const Image< D > &	img,
		float	radius
	)

Returns the mean filtered image with the given radius.

Date: 2014/Jan/08

Parameters

img	Input image.
neighborhood_radius	radius of the neighborhood.

Returns: Mean filtered image with the given radius.

Warning: none.

template<class D >

Image< D > Bial::Filtering::Mean	(	const Image< D > &	img,
		const Image< D > &	msk,
		float	radius
	)

Returns the mean filtered image with the given radius restricted to non-zero mask pixels.

Date: 2014/Jan/08

Parameters

img	Input image.
msk	Restrictive mask.
neighborhood_radius	radius of the neighborhood.

Returns: Mean filtered image with the given radius restricted to non-zero mask pixels.

Warning: none.

template<class D >

Image< D > Bial::Filtering::Median	(	const Image< D > &	img,
		float	radius
	)

Returns the median filtered image with the given radius.

Date: 2013/Aug/08

Parameters

img	Input image.
neighborhood_radius	radius of the neighborhood.

Returns: Median filtered image with the given radius.

Warning: none.

template<class D >

void Bial::Filtering::MedianThreads	(	const Image< D > &	img,
		const Adjacency &	adj,
		Image< D > &	res,
		size_t	thread,
		size_t	total_threads
	)

Multi-thread implementation of the median filtered image with the given radius.

Date: 2013/Aug/08

Parameters

img	Input image.
adj	Adjacency relation.
res	Resulting image.
thread	number of the thread.
total_threads	total number of threads.

Returns: none.

Warning: none.

template<class D >

Image< D > Bial::Filtering::OptimalAnisotropicDiffusion	(	Image< D >	img,
		const DiffusionFunction *	diff_func,
		float	radius,
		float	conservativeness
	)

Threads implementation for anisotropic diffusion filter.

Date: 2013/Dec/06

Parameters

img	Input image.
diff_function	diffusion function.
radius	radius of the adjacency relation.
conservativeness	Conservativeness function. Expected values: 0.0 to 1.0. Lower values keep weak edges and higher values remove stronger noise incidence.

Returns: none.

Warning: none.

template<class D >

Image< D > Bial::Filtering::OptimalAnisotropicDiffusion	(	Image< D >	img,
		const DiffusionFunction *	diff_func,
		float	radius,
		float	conservativeness,
		const Image< D > &	canny,
		const Image< D > &	backg
	)

Threads implementation for anisotropic diffusion filter.

Date: 2013/Dec/03

Parameters

img	Input image.
diff_function	diffusion function.
radius	radius of the adjacency relation.
conservativeness	Conservativeness function. Expected values: 0.0 to 1.0. Lower values keep weak edges and higher values remove stronger noise incidence.
canny	Canny edges segmentation.
backg	Image background segmentation.

Returns: none.

Warning: none.

Functions

Function Documentation