doi: 10.7763/IJFCC.2013.V2.120
A Single-Image Super-Resolution Method for Texture Interpolation
Yaron Kalit
,
Moshe Porat
- Department of Electrical Engineering, Technion, Haifa 32000, Israel.
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.
Keywords
- Image processing
- super resolution
- texture interpolation
- color zooming
How to 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. https://doi.org/ 10.7763/IJFCC.2013.V2.120
Copyright & License
Copyright © 2013 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).