Vector Subdivision Schemes for Arbitrary Matrix Masks

TL;DR

This paper introduces a general framework for vector subdivision schemes with arbitrary matrix masks, establishing their convergence properties and linking them to vector cascade algorithms, thus broadening the understanding beyond Hermite schemes.

Contribution

It defines a new vector subdivision scheme for any matrix mask and proves its convergence is equivalent to that of the associated cascade algorithm, generalizing previous results.

Findings

Established a unique way to define vector subdivision schemes for arbitrary matrix masks.

Proved convergence of the scheme is equivalent to convergence of the vector cascade algorithm.

Provided examples illustrating convergence rates for various schemes.

Abstract

Employing a matrix mask, a vector subdivision scheme is a fast iterative averaging algorithm to compute refinable vector functions for wavelet methods in numerical PDEs and to produce smooth curves in CAGD. In sharp contrast to the well-studied scalar subdivision schemes, vector subdivision schemes are much less well understood, e.g., Lagrange and (generalized) Hermite subdivision schemes are the only studied vector subdivision schemes in the literature. Because many wavelets used in numerical PDEs are derived from refinable vector functions whose matrix masks are not from Hermite subdivision schemes, it is necessary to introduce and study vector subdivision schemes for any general matrix masks in order to compute wavelets and refinable vector functions efficiently. For a general matrix mask, we show that there is only one meaningful way of defining a vector subdivision scheme. Motivated by vector cascade algorithms and recent study on Hermite subdivision schemes, we shall define a vector subdivision scheme for any arbitrary matrix mask and then we prove that the convergence of the newly defined vector subdivision scheme is equivalent to the convergence of its associated vector cascade algorithm. We also study convergence rates of vector subdivision schemes. The results of this paper not only bridge the gaps and establish intrinsic links between vector subdivision schemes and vector cascade algorithms but also strengthen and generalize current known results on Lagrange and (generalized) Hermite subdivision schemes. Several examples are provided to illustrate the results in this paper on various types of vector subdivision schemes with convergence rates.