Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
532661 | Pattern Recognition | 2009 | 12 Pages |
Abstract
Image registration is central to different applications such as medical analysis, biomedical systems, and image guidance. In this paper we propose a new algorithm for multimodal image registration. A Bayesian formulation is presented in which a likelihood term is defined using an observation model based on coefficient and geometric fields. These coefficients, which represent the local intensity polynomial transformations, as the local geometric transformations, are modeled as prior information by means of Markov random fields. This probabilistic approach allows one to find optimal estimators by minimizing an energy function in terms of both fields, making the registration between the images possible.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Edgar R. Arce-Santana, Alfonso Alba,