cv::StereoSGBM Class Reference

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

#include <opencv2/calib3d.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

Member Enumeration Documentation

anonymous enum

anonymous enum

Enumerator
MODE_SGBM
MODE_HH
MODE_SGBM_3WAY
MODE_HH4

Member Function Documentation

create()

static Ptr< StereoSGBM > cv::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  )

static

Python:
	cv.StereoSGBM.create(	[, minDisparity[, numDisparities[, blockSize[, P1[, P2[, disp12MaxDiff[, preFilterCap[, uniquenessRatio[, speckleWindowSize[, speckleRange[, mode]]]]]]]]]]]	) ->	retval
	cv.StereoSGBM_create(	[, minDisparity[, numDisparities[, blockSize[, P1[, P2[, disp12MaxDiff[, preFilterCap[, uniquenessRatio[, speckleWindowSize[, speckleRange[, mode]]]]]]]]]]]	) ->	retval

Creates StereoSGBM object.

Parameters

minDisparity	Minimum possible disparity value. Normally, it is zero but sometimes rectification algorithms can shift images, so this parameter needs to be adjusted accordingly.
numDisparities	Maximum disparity minus minimum disparity. The value is always greater than zero. In the current implementation, this parameter must be divisible by 16.
blockSize	Matched block size. It must be an odd number >=1 . Normally, it should be somewhere in the 3..11 range.
P1	The first parameter controlling the disparity smoothness. See below.
P2	The second parameter controlling the disparity smoothness. The larger the values are, the smoother the disparity is. P1 is the penalty on the disparity change by plus or minus 1 between neighbor pixels. P2 is the penalty on the disparity change by more than 1 between neighbor pixels. The algorithm requires P2 > P1 . See stereo_match.cpp sample where some reasonably good P1 and P2 values are shown (like 8*number_of_image_channels*blockSize*blockSize and 32*number_of_image_channels*blockSize*blockSize , respectively).
disp12MaxDiff	Maximum allowed difference (in integer pixel units) in the left-right disparity check. Set it to a non-positive value to disable the check.
preFilterCap	Truncation value for the prefiltered image pixels. The algorithm first computes x-derivative at each pixel and clips its value by [-preFilterCap, preFilterCap] interval. The result values are passed to the Birchfield-Tomasi pixel cost function.
uniquenessRatio	Margin in percentage by which the best (minimum) computed cost function value should "win" the second best value to consider the found match correct. Normally, a value within the 5-15 range is good enough.
speckleWindowSize	Maximum size of smooth disparity regions to consider their noise speckles and invalidate. Set it to 0 to disable speckle filtering. Otherwise, set it somewhere in the 50-200 range.
speckleRange	Maximum disparity variation within each connected component. If you do speckle filtering, set the parameter to a positive value, it will be implicitly multiplied by 16. Normally, 1 or 2 is good enough.
mode	Set it to StereoSGBM::MODE_HH to run the full-scale two-pass dynamic programming algorithm. It will consume O(W*H*numDisparities) bytes, which is large for 640x480 stereo and huge for HD-size pictures. By default, it is set to false .

The first constructor initializes StereoSGBM with all the default parameters. So, you only have to set StereoSGBM::numDisparities at minimum. The second constructor enables you to set each parameter to a custom value.

getMode()

virtual int cv::StereoSGBM::getMode ( ) const

pure virtual

Python:
	cv.StereoSGBM.getMode(		) ->	retval

getP1()

virtual int cv::StereoSGBM::getP1 ( ) const

pure virtual

Python:
	cv.StereoSGBM.getP1(		) ->	retval

getP2()

virtual int cv::StereoSGBM::getP2 ( ) const

pure virtual

Python:
	cv.StereoSGBM.getP2(		) ->	retval

getPreFilterCap()

virtual int cv::StereoSGBM::getPreFilterCap ( ) const

pure virtual

Python:
	cv.StereoSGBM.getPreFilterCap(		) ->	retval

getUniquenessRatio()

virtual int cv::StereoSGBM::getUniquenessRatio ( ) const

pure virtual

Python:
	cv.StereoSGBM.getUniquenessRatio(		) ->	retval

setMode()

virtual void cv::StereoSGBM::setMode ( int  mode )

pure virtual

Python:
	cv.StereoSGBM.setMode(	mode	) ->	None

setP1()

virtual void cv::StereoSGBM::setP1 ( int  P1 )

pure virtual

Python:
	cv.StereoSGBM.setP1(	P1	) ->	None

setP2()

virtual void cv::StereoSGBM::setP2 ( int  P2 )

pure virtual

Python:
	cv.StereoSGBM.setP2(	P2	) ->	None

setPreFilterCap()

virtual void cv::StereoSGBM::setPreFilterCap ( int  preFilterCap )

pure virtual

Python:
	cv.StereoSGBM.setPreFilterCap(	preFilterCap	) ->	None

setUniquenessRatio()

virtual void cv::StereoSGBM::setUniquenessRatio ( int  uniquenessRatio )

pure virtual

Python:
	cv.StereoSGBM.setUniquenessRatio(	uniquenessRatio	) ->	None

---

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

• opencv2/calib3d.hpp