Recovery problem of parametrizations from Legendre data

Abstract

The problem of recovery of parametrizations from Legendre data is a very important inverse problem. In this paper, we provide a systematic and widely-applicable method to recover parametrizations $f: U_n \to \mathbb{R}^{n+1}$ from Legendre data where $U_n$ is an open subset of $\mathbb R^n$. Namely, for a dense subset of the space of real-analytic parametrizations from $U_n$ into $\mathbb{R}^{n+1}$, we show how to recover the parametrization from the Gauss mapping and the height function. Moreover, in order to assist readers to apply results of this paper, many concrete examples are given.