machinevisiontoolbox.Image.stereo_SGBM

Image.stereo_SGBM(right, hw, drange, speckle=None)

Stereo semi-global block matching

Parameters:

  • right (Image) – right image

  • hw (int) – window half width

  • drange (array_like(2)) – disparity range

  • speckle (array_like(2), optional) – speckle filter parameters, defaults to None

Raises:

ValueError – block size too small

Returns:

disparity image

Return type:

Image

This is an efficient semi-global block-matching stereo implementation. It returns the disparity image, same size as input images, whose elements give the subpixel-interpolated disparity (in pixels) of the corresponding point in the left image.

Speckle are small regions of anomalous disparity. A speckle is defined as less than A pixels with disparity variation less than V, and the filter parameters are (A, V). The disparity values within a detected speckle are set to that of its enclosing region.

Example:

>>> rocks_l = Image.Read("rocks2-l.png", reduce=2)
>>> rocks_r = Image.Read("rocks2-r.png", reduce=2)
>>> disparity = rocks_l.stereo_SGBM(rocks_r, hw=3, drange=[40, 90], speckle=(200, 2))
Note:

The images are assumed to be epipolar aligned.

References:

  • Stereo processing by semiglobal matching and mutual information, Heiko Hirschmuller, IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(2):328–341, 2008.

  • Robotics, Vision & Control for Python, Section 14.4.2.7, P. Corke, Springer 2023.

Seealso:

stereo_SGBM stereo_simple opencv.StereoSGBM