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Uncalibrated stereo rectification

Since R2022b



[tform1,tform2] = estimateStereoRectification(F,inlierPoints1,inlierPoints2,imageSize) returns projective transformations for rectifying stereo images. This function does not require intrinsic or extrinsic camera parameters.


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Load the stereo images and feature points which are already matched.

I1 = imread("yellowstone_left.png");
I2 = imread("yellowstone_right.png");
load yellowstone_inlier_points;

Display point correspondences. Notice that the matching points are in different rows, indicating that the stereo pair is not rectified.

title("Original Images and Matching Feature Points");

Calculate the fundamental matrix from the corresponding points.

f = estimateFundamentalMatrix(inlier_points1,inlier_points2, ...

Calculate the rectification transformations.

[tform1,tform2] = estimateStereoRectification(f,inlier_points1,...

Rectify the stereo images using projective transformations tform1 and tform2.

[I1Rect,I2Rect] = rectifyStereoImages(I1,I2,tform1,tform2);

Display the stereo anaglyph, which can also be viewed with 3-D glasses.


Input Arguments

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Fundamental matrix for the stereo images, specified as a 3-by-3 matrix. The fundamental matrix satisfies this criteria for P1, a point in image 1, and P2, a corresponding point in image 2:

[P2,1] * F * [P1,1]' = 0

Data Types: single | double

Coordinates of points in image 1, specified as an M-by-2 matrix of M number of [x y] coordinates, or as one of the point feature objects described in Point Feature Types.

Coordinates of corresponding points in image 2, specified as an M-by-2 matrix of M number of [x y] coordinates, or as one of the point feature objects described in Point Feature Types.

Size of image 2, specified as a numeric vector in the format returned by the size function.

Output Arguments

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Projective transformation 1 describing the projective transformations for input image 1, returned as a projtform2d object.

Projective transformation 2 describing the projective transformations for input image 2, returned as a projtform2d object.


  • Applying the output uncalibrated rectification of tform1 (or tform2) to image 1 (or image 2) can result in an undesired distortion if an epipole exists within the image. You can check for an epipole within an image by applying the isEpipoleInImage function.


[1] Hartley, Richard, and Andrew Zisserman. Multiple View Geometry in Computer Vision. 2nd ed. Cambridge, UK ; New York: Cambridge University Press, 2003.

[2] Pollefeys, M., Koch, R., and Van Gool, L.. A Simple and Efficient Rectification Method for General Motion. Proceedings of the Seventh IEEE International Conference on Computer Vision. Volume 1, pages 496-501. 1999. DOI:10.1109/ICCV.1999.791262.

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

Version History

Introduced in R2022b

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