Fractional Regularization Term for Variational Image Registration

Mathematical Problems in Engineering. 2009;2009 DOI 10.1155/2009/707026

 

Journal Homepage

Journal Title: Mathematical Problems in Engineering

ISSN: 1024-123X (Print); 1563-5147 (Online)

Publisher: Hindawi Publishing Corporation

LCC Subject Category: Technology: Engineering (General). Civil engineering (General) | Science: Mathematics

Country of publisher: Egypt

Language of fulltext: English

Full-text formats available: PDF, HTML, ePUB, XML

 

AUTHORS

Rafael Verdú-Monedero (Department of Information Technologies and Communications, Technical University of Cartagena, Cartagena 30202, Spain)
Jorge Larrey-Ruiz (Department of Information Technologies and Communications, Technical University of Cartagena, Cartagena 30202, Spain)
Juan Morales-Sánchez (Department of Information Technologies and Communications, Technical University of Cartagena, Cartagena 30202, Spain)
José Luis Sancho-Gómez (Department of Information Technologies and Communications, Technical University of Cartagena, Cartagena 30202, Spain)

EDITORIAL INFORMATION

Blind peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 26 weeks

 

Abstract | Full Text

Image registration is a widely used task of image analysis with applications in many fields. Its classical formulation and current improvements are given in the spatial domain. In this paper a regularization term based on fractional order derivatives is formulated. This term is defined and implemented in the frequency domain by translating the energy functional into the frequency domain and obtaining the Euler-Lagrange equations which minimize it. The new regularization term leads to a simple formulation and design, being applicable to higher dimensions by using the corresponding multidimensional Fourier transform. The proposed regularization term allows for a real gradual transition from a diffusion registration to a curvature registration which is best suited to some applications and it is not possible in the spatial domain. Results with 3D actual images show the validity of this approach.