Surface smoothing with B-spline finite elements

Monotone B-spline Smoothing

Estimation of growth curves or item response curves often involves monotone data smoothing. Methods that have been studied in the literature tend to be either less exible or more diicult to compute when constraints such as monotonicity are incorporated. Built upon the ideas of Ramsay (1988) and Koenker, Ng and Portnoy (1994), we propose monotone B-spline smoothing based on L 1 optimization. It ...

Robust B-Spline Image Smoothing

In this work we present a new approach to two dimensional robust spline smoothing. The proposed method is based on M-estimator algorithms but unlike in other M-estimator based image processing algorithms it takes into consideration spatial relations between picture elements. The contribution of the sample to the model depends not only on the current residual of that sample, but also on the neig...

B-spline Curve Smoothing for Isobathymetric Line Generalization

This paper introduces a new method for curve smoothing which is specific for isobathymetric line generalization. Isobaths are modeled with B-spline curves that can maintain the smooth feature of the curves. Smoothing is performed by keeping the curve points always on the deepest side of the original curve so that the result is consistent with the safety constraint. It is done by using a snake m...

Smoothing by Spline Functions

B-Spline Smoothing of Feature Vectors in Nonnegative Matrix Factorization

Nonnegative Matrix Factorization (NMF) captures nonnegative, sparse and parts-based feature vectors from the set of observed nonnegative vectors. In many applications, the features are also expected to be locally smooth. To incorporate the information on the local smoothness to the optimization process, we assume that the features vectors are conical combinations of higher degree B-splines with...