Abstract
A super-resolution image reconstruction al- gorithm using natural neighbor interpolation is proposed and its performance is evaluated. The algorithm is di- vided into two stages: image registration and the recon- struction of a high-resolution color image. In the first stage, as shifts between images are usually unknown, the algorithm computes an approximation of these dis- placements by solving the system of linear equations proposed by Keren, Peleg, and Brada, then the pixels of all low-resolution images are mapped into a high- resolution grid by computing the new coordinates using the motion vectors. In the second stage, the pixel val- ues that match the high-resolution grid are interpolated using natural neighbor interpolation which is a weighted average interpolation method for scattered data, based in the areas of the Voronoi polygons of the neighboring pixels. Finally, the proposed natural neighbor super- resolution algorithm is compared with some popular super-resolution algorithms presented in literature.
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