A deformable grid approach for Bayesian image registration

Authors:
Michele Ceccarelli;Michele Donatiello
Affiliations:
University of Sannio, Benevento, Italy;University of Sannio, Benevento, Italy
Venue:
SPPRA '08 Proceedings of the Fifth IASTED International Conference on Signal Processing, Pattern Recognition and Applications
Year:
2008

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Abstract

The paper presents a novel non parametric image registration method based on an explicit representation of the warping function. The image registration problem is approached in the Bayesian framework with a prior term given by a Gaussian random field accounting the regularity of a deformable grid. The algorithm is completely unsupervised, making it suitable for high throughput biomedical applications such as proteomics and cellular imaging.