Interface for Adaptive Manifold Filter realizations. More...

#include "edge_filter.hpp"

Inheritance diagram for cv::ximgproc::AdaptiveManifoldFilter:

Public Member Functions
virtual void	collectGarbage ()=0

virtual void	filter (InputArray src, OutputArray dst, InputArray joint=noArray())=0
	Apply high-dimensional filtering using adaptive manifolds. More...

virtual bool	getAdjustOutliers () const =0

virtual int	getPCAIterations () const =0

virtual double	getSigmaR () const =0

virtual double	getSigmaS () const =0

virtual int	getTreeHeight () const =0

virtual bool	getUseRNG () const =0

virtual void	setAdjustOutliers (bool val)=0

virtual void	setPCAIterations (int val)=0

virtual void	setSigmaR (double val)=0

virtual void	setSigmaS (double val)=0

virtual void	setTreeHeight (int val)=0

virtual void	setUseRNG (bool val)=0

Public Member Functions inherited from cv::Algorithm
	Algorithm ()

virtual	~Algorithm ()

virtual void	clear ()
	Clears the algorithm state. More...

virtual bool	empty () const
	Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. More...

virtual String	getDefaultName () const

virtual void	read (const FileNode &fn)
	Reads algorithm parameters from a file storage. More...

virtual void	save (const String &filename) const

virtual void	write (FileStorage &fs) const
	Stores algorithm parameters in a file storage. More...

Static Public Member Functions
static Ptr < AdaptiveManifoldFilter >	create ()

Static Public Member Functions inherited from cv::Algorithm
template<typename _Tp >
static Ptr< _Tp >	load (const String &filename, const String &objname=String())
	Loads algorithm from the file. More...

template<typename _Tp >
static Ptr< _Tp >	loadFromString (const String &strModel, const String &objname=String())
	Loads algorithm from a String. More...

template<typename _Tp >
static Ptr< _Tp >	read (const FileNode &fn)
	Reads algorithm from the file node. More...

Detailed Description

Interface for Adaptive Manifold Filter realizations.

For more details about this filter see [50] and References_.

Below listed optional parameters which may be set up with Algorithm::set function.

member double sigma_s = 16.0 Spatial standard deviation.
member double sigma_r = 0.2 Color space standard deviation.
member int tree_height = -1 Height of the manifold tree (default = -1 : automatically computed).
member int num_pca_iterations = 1 Number of iterations to computed the eigenvector.
member bool adjust_outliers = false Specify adjust outliers using Eq. 9 or not.
member bool use_RNG = true Specify use random number generator to compute eigenvector or not.