A survey of image registration techniques
ACM Computing Surveys (CSUR)
Across-modality registration using intensity-based cost functions
Handbook of medical imaging
Alignment by maximization of mutual information
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Hidden Markov Measure Field Models for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Analysis, Random Fields and Markov Chain Monte Carlo Methods: A Mathematical Introduction (Stochastic Modelling and Applied Probability)
Image registration using Markov random coefficient fields
IWCIA'08 Proceedings of the 12th international conference on Combinatorial image analysis
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
A non-rigid multimodal image registration method based on particle filter and optical flow
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I
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Image Registration is a central task to different applications, such as medical image analysis, stereo computer vision, and optical flow estimation. One way to solve this problem consists in using Bayesian Estimation theory. Under this approach, this work introduces a new alternative, based on Particle Filters, which have been previously used to estimate the states of dynamic systems. For this work, we have adapted the Particle Filter to carry out the registration of unimodal and multimodal images, and performed a series of preliminary tests, where the proposed method has proved to be efficient, robust, and easy to implement.