Oversampling in shift-invariant spaces with a rational sampling period
IEEE Transactions on Signal Processing
On the role of exponential splines in image interpolation
IEEE Transactions on Image Processing
Quasi-interpolation by means of filter-banks
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Proceedings of the 26th Spring Conference on Computer Graphics
Quasi-interpolation on the body centered cubic lattice
EuroVis'09 Proceedings of the 11th Eurographics / IEEE - VGTC conference on Visualization
Rendering in shift-invariant spaces
Proceedings of Graphics Interface 2013
Hi-index | 0.02 |
The reconstruction of a continuous-domain representation from sampled data is an essential element of many image processing tasks, in particular, image resampling. Until today, most image data have been available on Cartesian lattices, despite the many theoretical advantages of hexagonal sampling. In this paper, we propose new reconstruction methods for hexagonally sampled data that use the intrinsically 2-D nature of the lattice, and that at the same time remain practical and efficient. To that aim, we deploy box-spline and hex-spline models, which are notably well adapted to hexagonal lattices. We also rely on the quasi-interpolation paradigm to design compelling prefilters; that is, the optimal filter for a prescribed design is found using recent results from approximation theory. The feasibility and efficiency of the proposed methods are illustrated and compared for a hexagonal to Cartesian grid conversion problem