Semiparametric estimation of shifts on compact Lie groups for image registration

• 成果类型: Article
• 署名作者: Bigot, Jeremie; Loubes, Jean-Michel; Vimond, Myriam
• 署名单位: Universite de Toulouse; Universite Toulouse III - Paul Sabatier; Ecole Nationale de la Statistique et de l'Analyse de l'Information (ENSAI)
• 刊物名称: PROBABILITY THEORY AND RELATED FIELDS
• ISSN/ISSBN: 0178-8051
• DOI: 10.1007/s00440-010-0327-2
• 发表日期: 2012
• 页码: 425-473
• 关键词: extrinsic sample means; MANIFOLDS; location; models

摘要

In this paper we focus on estimating the deformations that may exist between similar images in the presence of additive noise when a reference template is unknown. The deformations are modeled as parameters lying in a finite dimensional compact Lie group. A general matching criterion based on the Fourier transform and its well known shift property on compact Lie groups is introduced. M-estimation and semiparametric theory are then used to study the consistency and asymptotic normality of the resulting estimators. As Lie groups are typically nonlinear spaces, our tools rely on statistical estimation for parameters lying in a manifold and take into account the geometrical aspects of the problem. Some simulations are used to illustrate the usefulness of our approach and applications to various areas in image processing are discussed.