Fast image polynomial spline interpolation algorithm with shape-preserving properties Original Research Article

In this article, we address the problem of interpolating data points by regular image-spline polynomial curves of smoothness image, image, that are invariant under rotation of the data. To obtain a image cubic interpolating curve, we use a local minimization method in parallel on five data points belonging to a sliding window. This procedure is extended to create image-continuous image splines, image, on larger windows. We show that, in the image-continuous (image) interpolation case, this local minimization method preserves the linear parts of the data well, while a global image minimization method does not in general do so. The computational complexity of the procedure is linear in the global number of data points, no matter what the order image of smoothness of the curve is.