Global volumetric image registration using local linear property of image manifold

Abstract

We propose a three-dimensional global image registration method for a sparse dictionary. To achieve robust and accurate registration, which based on template matching, a large number of transformed images are prepared and stored in the dictionary. To reduce the spatial complexity of this image dictionary, we introduce a method of generating a new template image from a collection of images stored in the image dictionary. This generated template image allows us to achieve accurate image registration even if the population of the image dictionary is relatively small and the template has a small pattern perturbation. To further reduce the complexity, we compute a matching process in a low-dimensional Euclidean space projected by a random projection.