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2-D local weighted mean geometric transformation

A `LocalWeightedMeanTransformation2D`

object encapsulates a
2-D local weighted mean geometric transformation.

You can create a `LocalWeightedMeanTransformation2D`

object using the
following methods:

The

`fitgeotrans`

function, which estimates a geometric transformation that maps pairs of control points between two images.The

`images.geotrans.LocalWeightedMeanTransformation2D`

described here. This function creates a`LocalWeightedMeanTransformation2D`

object using coordinates of fixed points and moving points, and a specified number of points to use in the local weighted mean calculation.

`tform = images.geotrans.LocalWeightedMeanTransformation2D(movingPoints,fixedPoints,n)`

`tform = images.geotrans.LocalWeightedMeanTransformation2D(`

creates a `movingPoints`

,`fixedPoints`

,`n`

)`LocalWeightedMeanTransformation2D`

object given control point coordinates in `movingPoints`

and
`fixedPoints`

, which define matched control points in the
moving and fixed images, respectively. The `n`

closest points
are used to infer a second degree polynomial transformation for each control
point pair.

`outputLimits` | Find output spatial limits given input spatial limits |

`transformPointsInverse` | Apply inverse geometric transformation |

The local weighted mean transformation infers a polynomial at each control point using
neighboring control points. The mapping at any location depends on a weighted average of
these polynomials. The `n`

closest points are used to infer a second
degree polynomial transformation for each control point pair. `n`

can
be as small as 6, but making it small risks generating ill-conditioned
polynomials.