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2011

A non-neighbourhood super-resolution using phantom hashing

Author:Kathiravan S and J. Kanakaraj

Abstract:
Super-resolution is the process of creating an high resolution image from a low resolution input sequence. To overcome the difficulties of good image registration, several methods have been proposed exploiting the non-neighbourhood intuition, i.e. any data-point can contribute to the ï¬nal result if it is relevant. These algorithms however limit in practice the search region for relevant points in order to lower the corresponding computational cost. Furthermore, they deï¬ne the non-neighbourhood relations in the high resolution space, where the true images are unknown. In this work, we introduce the use of phantom hashing to efficiently compute fully non-neighbourhood neighbours. We also restate the super-resolution functional using ï¬xed weights in the low resolution space, allowing us to use resolution schemes that avoid many artifacts.