Opencv: StereoSGBM and StereoBinarySGBM is it different?

[LaurentBerger]

Hi,

Are StereoBM and StereoBinaryBM classes differents?
Are StereoSGBM and StereoBinarySGBM classes differents?

I can find in doc cv::StereoSGBM Class Reference in calib3d module (opencv)

Detailed Description

The class implements the modified H. Hirschmuller algorithm [75] 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 [13] 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

and cv::stereo::StereoBinarySGBM in stereo module (opencv_contrib)

Detailed Description

The class implements the modified H. Hirschmuller algorithm [75] 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 [13] 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/python2/stereo_match.py

Same thing for cv::StereoBM Class Reference

Detailed Description

Class for computing stereo correspondence using the block matching algorithm, introduced and contributed to OpenCV by K. Konolige.

and cv::stereo::StereoBinaryBM Class Reference

Detailed Description

Class for computing stereo correspondence using the block matching algorithm, introduced and contributed to OpenCV by K. Konolige.

[sovrasov]

Author of contrib stereo module copied docs from the calib3d module without any change, so descriptions are the same but the algorithms differ.