Improved optimization methods for image registration problems

Chen, Ke and Grapiglia, Geovani Nunes and Yuan, Jinyun and Zhang, Daoping (2019) Improved optimization methods for image registration problems. Numerical Algorithms, 80 (2). pp. 305-336. ISSN 1017-1398 (https://doi.org/10.1007/s11075-018-0486-2)

[thumbnail of Chen-etal-NA-2019-Improved-optimization-methods-for-image-registration-problems]
Preview
Text. Filename: Chen-etal-NA-2019-Improved-optimization-methods-for-image-registration-problems.pdf
Accepted Author Manuscript
License: Strathprints license 1.0

Download (10MB)| Preview

Abstract

In this paper, we propose new multilevel optimization methods for minimizing continuously differentiable functions obtained by discretizing models for image registration problems. These multilevel schemes rely on a novel two-step Gauss-Newton method, in which a second step is computed within each iteration by minimizing a quadratic approximation of the objective function over a certain two-dimensional subspace. Numerical results on image registration problems show that the proposed methods can outperform the standard multilevel Gauss-Newton method.