A compressed primal-dual method for generating bivariate cubic splines

In this paper, we develop a compressed version of the primal-dual interior point method for generating bivariate cubic L 1 splines. Discretization of the underlying optimization model, which is a nonsmooth convex programming problem, leads to an overdetermined linear system that can be handled by interior point methods. Taking advantage of the special matrix structure of the cubic L 1 spline problem, we design a compressed primal-dual interior point algorithm. Computational experiments indicate that this compressed primal-dual method is robust and is much faster than the ordinary (uncompressed) primal-dual interior point algorithm.