Abstract
Abstract Resampling is a common operation in digital image processing systems. The standard procedure involves the (conceptual) reconstruction of a continuous image succeeded by sampling on the new lattice sites. When the reconstruction is done by classical interpolation functions, results might be sub-optimal because the information loss is not minimized. In the particular case of subsampling (i.e., resampling to a coarser lattice), aliasing artifacts might arise and produce disturbing moire patterns. This paper first introduces a spline model for different orders, both for orthogonal and hexagonal lattices. Next, an expression for a least-squares approximation is derived which can be applied to convolution-based resampling. Experimental results for a printing application demonstrate the feasibility of the proposed method and are compared against the standard approach. Our technique can be applied to general least-squares resampling between regular lattices.
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