| Surface spline transformation |
| Image Registration and Fusion Systems |
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Surface spline is a transformation defined by logarithmic basis functions and a linear term. The linear term makes it possible to
register images with linear geometric differences. Because logarithmic functions are radially symmetric, this function is particularly
suitable when the landmarks are rather uniformly spaced. If the density of landmarks varies across the image domain, large errors
may be obtained away from the landmarks. Also, since this transformation requires the solution of a system of equations, it is suitable
when a rather small set of landmarks, (fewer than 100) is available. When thousands of landmarks are available, this transformation
function not only becomes slow, the matrix of coefficients may become ill-conditioned, making it impossible to register the images.
When the landmarks are very irregularly spaced and a large number of them is available, piecewise-linear transformation is a better
choice when compared to surface spline.
To learn more about this and other transformation functions for image registration, see this report on Transformation Functions.
To obtain a license for this surface spline transformation, please follow the link =>
register images with linear geometric differences. Because logarithmic functions are radially symmetric, this function is particularly
suitable when the landmarks are rather uniformly spaced. If the density of landmarks varies across the image domain, large errors
may be obtained away from the landmarks. Also, since this transformation requires the solution of a system of equations, it is suitable
when a rather small set of landmarks, (fewer than 100) is available. When thousands of landmarks are available, this transformation
function not only becomes slow, the matrix of coefficients may become ill-conditioned, making it impossible to register the images.
When the landmarks are very irregularly spaced and a large number of them is available, piecewise-linear transformation is a better
choice when compared to surface spline.
To learn more about this and other transformation functions for image registration, see this report on Transformation Functions.
To obtain a license for this surface spline transformation, please follow the link =>