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General Information
    • ISSN: 2010-3751
    • Frequency: Bimonthly (2012-2016); Quarterly (Since 2017)
    • DOI: 10.18178/IJFCC
    • Editor-in-Chief: Prof. Mohamed Othman
    • Executive Editor: Ms. Cherry L. Chan
    • Abstracting/ Indexing: Google Scholar,  Crossref, Electronic Journals LibraryEI (INSPEC, IET), etc.
    • E-mail:  ijfcc@ejournal.net 
Prof. Mohamed Othman
Department of Communication Technology and Network Universiti Putra Malaysia, Malaysia
It is my honor to be the editor-in-chief of IJFCC. The journal publishes good papers in the field of future computer and communication. Hopefully, IJFCC will become a recognized journal among the readers in the filed of future computer and communication.
IJFCC 2013 Vol.2(1): 54-58 ISSN: 2010-3751
DOI: 10.7763/IJFCC.2013.V2.120

A Single-Image Super-Resolution Method for Texture Interpolation

Yaron Kalit and Moshe Porat
Abstract—In recent years, a number of super-resolution techniques have been proposed. Most of these techniques construct a high resolution image by either combining several low resolution images at sub-pixel misalignments or by learning correspondences between low and high resolution image pairs. In this paper we present a stochastic super-resolution method for color textures from a single image. The proposed algorithm takes advantage of the repetitive nature of textures and the existence of several similar patches within the texture, as well as the color-intensity correlation that often exist in natural images. In the first step of the algorithm the intensity component is interpolated. For each pixel, the missing value is chosen according to a probability distribution constructed from a measure of similarity to other patches in the texture as well as from local features and patch color similarity. In the second stage, the color components are interpolated in a similar manner, using patches of the color channels as well as the already interpolated intensity values. Our conclusion is that the proposed approach outperforms presently available methods.

Index Terms—Image processing, super resolution, texture interpolation, color zooming.

This research was supported in part by Technion's fund #7110134 and by the Ollendorff Minerva Center. Minerva is funded through the BMBF.
The authors are with the Department of Electrical Engineering, Technion, Haifa 32000, Israel (e-mail: ykalit@tx.technion.ac.il, mp@ee.technion.ac.il).


Cite: Yaron Kalit and Moshe Porat, "A Single-Image Super-Resolution Method for Texture Interpolation," International Journal of Future Computer and Communication vol. 2, no. 1 pp. 54-58, 2013.
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