A Super-Resolution Image Reconstruction using Natural Neighbor Interpolation

Abstract

A super-resolution image reconstruction algorithm using the natural neighbor interpolation is proposed and its performance is evaluated.The algorithm is divided into two stages: image registration and the reconstruction of a high-resolution color image.In a first stage, as shifts between images are usually unknown, the algorithm computes an approximation of these displacements 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 a second stage, the pixel values that match the high-resolution grid are interpolated using the 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 natural neighbor super-resolution algorithm is compared with some popular super-resolution algorithms proposed in literature.