cv::StereoSGBM Class Reference

The class implements the modified H. Hirschmuller algorithm [126] that differs from the original one as follows: More...

#include <opencv2/stereo.hpp>

Collaboration diagram for cv::StereoSGBM:

Public Types
enum	{   MODE_SGBM = 0 ,   MODE_HH = 1 ,   MODE_SGBM_3WAY = 2 ,   MODE_HH4 = 3 }
Public Types inherited from cv::StereoMatcher
enum	{   DISP_SHIFT = 4 ,   DISP_SCALE = (1 << DISP_SHIFT) }

Public Member Functions
virtual int	getMode () const =0
virtual int	getP1 () const =0
virtual int	getP2 () const =0
virtual int	getPreFilterCap () const =0
virtual int	getUniquenessRatio () const =0
virtual void	setMode (int mode)=0
virtual void	setP1 (int P1)=0
virtual void	setP2 (int P2)=0
virtual void	setPreFilterCap (int preFilterCap)=0
virtual void	setUniquenessRatio (int uniquenessRatio)=0
Public Member Functions inherited from cv::StereoMatcher
virtual void	compute (InputArray left, InputArray right, OutputArray disparity)=0
	Computes disparity map for the specified stereo pair.
virtual int	getBlockSize () const =0
virtual int	getDisp12MaxDiff () const =0
virtual int	getMinDisparity () const =0
virtual int	getNumDisparities () const =0
virtual int	getSpeckleRange () const =0
virtual int	getSpeckleWindowSize () const =0
virtual void	setBlockSize (int blockSize)=0
virtual void	setDisp12MaxDiff (int disp12MaxDiff)=0
virtual void	setMinDisparity (int minDisparity)=0
virtual void	setNumDisparities (int numDisparities)=0
virtual void	setSpeckleRange (int speckleRange)=0
virtual void	setSpeckleWindowSize (int speckleWindowSize)=0
Public Member Functions inherited from cv::Algorithm
	Algorithm ()
virtual	~Algorithm ()
virtual void	clear ()
	Clears the algorithm state.
virtual bool	empty () const
	Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
virtual String	getDefaultName () const
virtual void	read (const FileNode &fn)
	Reads algorithm parameters from a file storage.
virtual void	save (const String &filename) const
void	write (const Ptr< FileStorage > &fs, const String &name=String()) const
virtual void	write (FileStorage &fs) const
	Stores algorithm parameters in a file storage.
void	write (FileStorage &fs, const String &name) const

Static Public Member Functions
static Ptr< StereoSGBM >	create (int minDisparity=0, int numDisparities=16, int blockSize=3, int P1=0, int P2=0, int disp12MaxDiff=0, int preFilterCap=0, int uniquenessRatio=0, int speckleWindowSize=0, int speckleRange=0, int mode=StereoSGBM::MODE_SGBM)
	Creates StereoSGBM object.
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.
template<typename _Tp >
static Ptr< _Tp >	loadFromString (const String &strModel, const String &objname=String())
	Loads algorithm from a String.
template<typename _Tp >
static Ptr< _Tp >	read (const FileNode &fn)
	Reads algorithm from the file node.

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

Detailed Description

The class implements the modified H. Hirschmuller algorithm [126] that differs from the original one as follows:

• By default, the algorithm is single-pass, which means that you consider only 5 directions instead of 8. Set mode=StereoSGBM::MODE_HH in createStereoSGBM to run the full variant of the algorithm but beware that it may consume a lot of memory.
• The algorithm matches blocks, not individual pixels. Though, setting blockSize=1 reduces the blocks to single pixels.
• Mutual information cost function is not implemented. Instead, a simpler Birchfield-Tomasi sub-pixel metric from [28] is used. Though, the color images are supported as well.
• Some pre- and post- processing steps from K. Konolige algorithm StereoBM are included, for example: pre-filtering (StereoBM::PREFILTER_XSOBEL type) and post-filtering (uniqueness check, quadratic interpolation and speckle filtering).

Note

• (Python) An example illustrating the use of the StereoSGBM matching algorithm can be found at opencv_source_code/samples/python/stereo_match.py

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

• opencv2/stereo.hpp