Sparse match interpolation algorithm based on modified locally-weighted affine estimator from [220] and Fast Global Smoother as post-processing filter. More...

#include <opencv2/ximgproc/sparse_match_interpolator.hpp>

Inheritance diagram for cv::ximgproc::EdgeAwareInterpolator:

Public Member Functions
virtual float	getFGSLambda ()=0

virtual float	getFGSSigma ()=0

virtual int	getK ()=0

virtual float	getLambda ()=0

virtual float	getSigma ()=0

virtual bool	getUsePostProcessing ()=0

virtual void	setCostMap (const Mat &_costMap)=0
	Interface to provide a more elaborated cost map, i.e. edge map, for the edge-aware term. This implementation is based on a rather simple gradient-based edge map estimation. To used more complex edge map estimator (e.g. StructuredEdgeDetection that has been used in the original publication) that may lead to improved accuracies, the internal edge map estimation can be bypassed here. More...

virtual void	setFGSLambda (float _lambda)=0
	Sets the respective fastGlobalSmootherFilter() parameter. More...

virtual void	setFGSSigma (float _sigma)=0

virtual void	setK (int _k)=0
	Parameter to tune the approximate size of the superpixel used for oversegmentation. More...

virtual void	setLambda (float _lambda)=0
	Lambda is a parameter defining the weight of the edge-aware term in geodesic distance, should be in the range of 0 to 1000. More...

virtual void	setSigma (float _sigma)=0
	Sigma is a parameter defining how fast the weights decrease in the locally-weighted affine fitting. Higher values can help preserve fine details, lower values can help to get rid of noise in the output flow. More...

virtual void	setUsePostProcessing (bool _use_post_proc)=0
	Sets whether the fastGlobalSmootherFilter() post-processing is employed. It is turned on by default. More...

Public Member Functions inherited from cv::ximgproc::SparseMatchInterpolator
virtual void	interpolate (InputArray from_image, InputArray from_points, InputArray to_image, InputArray to_points, OutputArray dense_flow)=0
	Interpolate input sparse matches. More...

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...

void	write (FileStorage &fs, const String &name) const

void	write (const Ptr< FileStorage > &fs, const String &name=String()) const

Additional Inherited Members
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...

Protected Member Functions inherited from cv::Algorithm
void	writeFormat (FileStorage &fs) const

Detailed Description

Sparse match interpolation algorithm based on modified locally-weighted affine estimator from [220] and Fast Global Smoother as post-processing filter.

Member Function Documentation

◆ getFGSLambda()

virtual float cv::ximgproc::EdgeAwareInterpolator::getFGSLambda ( )

pure virtual

Python:
	cv.ximgproc.EdgeAwareInterpolator.getFGSLambda(		) ->	retval

See also: setFGSLambda

◆ getFGSSigma()

virtual float cv::ximgproc::EdgeAwareInterpolator::getFGSSigma ( )

pure virtual

Python:
	cv.ximgproc.EdgeAwareInterpolator.getFGSSigma(		) ->	retval

See also: setFGSLambda

◆ getK()

virtual int cv::ximgproc::EdgeAwareInterpolator::getK ( )

pure virtual

Python:
	cv.ximgproc.EdgeAwareInterpolator.getK(		) ->	retval

See also: setK

◆ getLambda()

virtual float cv::ximgproc::EdgeAwareInterpolator::getLambda ( )

pure virtual

Python:
	cv.ximgproc.EdgeAwareInterpolator.getLambda(		) ->	retval

See also: setLambda

◆ getSigma()

virtual float cv::ximgproc::EdgeAwareInterpolator::getSigma ( )

pure virtual

Python:
	cv.ximgproc.EdgeAwareInterpolator.getSigma(		) ->	retval

See also: setSigma

◆ getUsePostProcessing()

virtual bool cv::ximgproc::EdgeAwareInterpolator::getUsePostProcessing ( )

pure virtual

Python:
	cv.ximgproc.EdgeAwareInterpolator.getUsePostProcessing(		) ->	retval

See also: setUsePostProcessing

◆ setCostMap()

virtual void cv::ximgproc::EdgeAwareInterpolator::setCostMap ( const Mat & _costMap )

pure virtual

Python:
	cv.ximgproc.EdgeAwareInterpolator.setCostMap(	_costMap	) ->	None

Interface to provide a more elaborated cost map, i.e. edge map, for the edge-aware term. This implementation is based on a rather simple gradient-based edge map estimation. To used more complex edge map estimator (e.g. StructuredEdgeDetection that has been used in the original publication) that may lead to improved accuracies, the internal edge map estimation can be bypassed here.

Parameters

_costMap a type CV_32FC1 Mat is required.

See also: cv::ximgproc::createSuperpixelSLIC

◆ setFGSLambda()

virtual void cv::ximgproc::EdgeAwareInterpolator::setFGSLambda ( float _lambda )

pure virtual

Python:
	cv.ximgproc.EdgeAwareInterpolator.setFGSLambda(	_lambda	) ->	None

Sets the respective fastGlobalSmootherFilter() parameter.

◆ setFGSSigma()

virtual void cv::ximgproc::EdgeAwareInterpolator::setFGSSigma ( float _sigma )

pure virtual

Python:
	cv.ximgproc.EdgeAwareInterpolator.setFGSSigma(	_sigma	) ->	None

See also: setFGSLambda

◆ setK()

virtual void cv::ximgproc::EdgeAwareInterpolator::setK ( int _k )

pure virtual

Python:
	cv.ximgproc.EdgeAwareInterpolator.setK(	_k	) ->	None

Parameter to tune the approximate size of the superpixel used for oversegmentation.

See also: cv::ximgproc::createSuperpixelSLICK is a number of nearest-neighbor matches considered, when fitting a locally affine model. Usually it should be around 128. However, lower values would make the interpolation noticeably faster.

◆ setLambda()

virtual void cv::ximgproc::EdgeAwareInterpolator::setLambda ( float _lambda )

pure virtual

Python:
	cv.ximgproc.EdgeAwareInterpolator.setLambda(	_lambda	) ->	None

Lambda is a parameter defining the weight of the edge-aware term in geodesic distance, should be in the range of 0 to 1000.

◆ setSigma()

virtual void cv::ximgproc::EdgeAwareInterpolator::setSigma ( float _sigma )

pure virtual

Python:
	cv.ximgproc.EdgeAwareInterpolator.setSigma(	_sigma	) ->	None

Sigma is a parameter defining how fast the weights decrease in the locally-weighted affine fitting. Higher values can help preserve fine details, lower values can help to get rid of noise in the output flow.

◆ setUsePostProcessing()

virtual void cv::ximgproc::EdgeAwareInterpolator::setUsePostProcessing ( bool _use_post_proc )

pure virtual

Python:
	cv.ximgproc.EdgeAwareInterpolator.setUsePostProcessing(	_use_post_proc	) ->	None

Sets whether the fastGlobalSmootherFilter() post-processing is employed. It is turned on by default.

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

opencv2/ximgproc/sparse_match_interpolator.hpp

Public Member Functions

Additional Inherited Members

Detailed Description

Member Function Documentation

◆ getFGSLambda()

◆ getFGSSigma()

◆ getK()

◆ getLambda()

◆ getSigma()

◆ getUsePostProcessing()

◆ setCostMap()

◆ setFGSLambda()

◆ setFGSSigma()

◆ setK()

◆ setLambda()

◆ setSigma()

◆ setUsePostProcessing()