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This paper presents a novel approach to single image super-resolution. We construct two pyramids: low-resolution image pyramid and the corresponding high-resolution image pyramid, then perform image segmentation and cluster the image patches according to a certain rule. We seek a sparse representation for each patch in pyramid via a corresponding dictionary. Our method aims to learn the relationship...
In this paper we present a novel method for single image super-resolution (SR). Given an input low-resolution image, we create a pyramid pair: the ground truth pyramid and the interpolated pyramid. This method aims to model the relationship between pixel value in ground truth pyramid and its corresponding 8- neighborhood vector in interpolated pyramid using Gaussian Mixture Model (GMM). Each pixel...
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