title: Bandlimited reconstruction of multidimensional images from irregular samples.
abstract: We examine different sampling lattices and their respective bandlimited spaces for reconstruction of irregularly sampled multidimensional images. Considering an irregularly sampled dataset, we demonstrate that the non-tensor-product bandlimited approximations corresponding to the body-centered cubic and face-centered cubic lattices provide a more accurate reconstruction than the tensor-product bandlimited approximation associated with the commonly-used Cartesian lattice. Our practical algorithm uses multidimensional sinc functions that are tailored to these lattices and a regularization scheme that provides a variational framework for efficient implementation. Using a number of synthetic and real data sets we record improvements in the accuracy of reconstruction in a practical setting.
authors.affiliation: Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL 32611, USA. xie@cise.ufl.edu
authors.forename: Xie
authors.initials: X
authors.lastname: Xu
authors.forename: Wenxing
authors.initials: W
authors.lastname: Ye
authors.forename: Alireza
authors.initials: A
authors.lastname: Entezari