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Control Point Registration

Image Processing Toolbox™ provides tools to support 2-D point mapping to determine the parameters of the transformation required to bring an image into alignment with another image. In point mapping, you pick pairs of control points in two images that identify the same features or landmarks in the images. Then, infer a geometric transformation from the positions of these control points. Finally, you apply the geometric transformation to the moving image, resulting in an image that is aligned with the fixed image.

The figure provides an illustration of this process. See Register Images with Projection Distortion Using Control Points for an extended example.

Select control points using cpselect, optionally fine tune the control points using cpcorr, estimate the transformation using fitgeotform2d, then warp the moving image using imwarp.

You may need to perform several iterations of this process, experimenting with different types of transformations, before you achieve a satisfactory result. Sometimes, you can perform successive registrations, removing gross global distortions first, and then removing smaller local distortions in subsequent passes.

To learn about 3-D point mapping, see fitgeotform3d (Medical Imaging Toolbox).

See Also

| | | | (Medical Imaging Toolbox)

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