TY - JOUR
T1 - A Robust Affine Image Registration Method
AU - N. Chumchob & K. Chen
JO - International Journal of Numerical Analysis and Modeling
VL - 2
SP - 311
EP - 334
PY - 2009
DA - 2009/06
SN - 6
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/ijnam/770.html
KW - Image registration, affine transformation, regularization, Newton method.
AB - <p style="text-align: justify;">Image registration has many real life applications. Affine image
registration is one of the commonly-used parametric models. Iterative solution methods for the underlying least squares problem suffer from convergence
problems whenever good initial guesses are not available. Variational models
are non-parametric deformable models that have been proposed based on least
squares fitting and regularization. The fast iterative solution methods often
require a reliable parametric (affine) method in a pre-registration step. In this
paper we first survey and study a class of methods suitable for providing the
good initial guesses for the affine model and a diffusion based variational model.
It appears that these initialization methods, while useful for many cases, are
not always reliable. Then we propose a regularized affine least squares approach that can overcome the convergence problems associated with existing
methods. Combined with a cooling idea in a multiresolution setting, it can
ensure robustness and selection of the optimal coupling parameter efficiently.
Numerical examples are given to demonstrate the effectiveness of our proposed
approach.</p>