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Singular value decomposition based fusion for super-resolution image reconstruction

Haidawati Binti Mohamad Nasir, H and Stankovic, Vladimir and Marshall, Stephen (2012) Singular value decomposition based fusion for super-resolution image reconstruction. Signal Processing: Image Communication, 27 (2). 180–191. ISSN 0923-5965

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Abstract

In this paper, we address a super-resolution problem of generating a high-resolution image from low-resolution images. The proposed super-resolution method consists of three steps: image registration, singular value decomposition (SVD)-based image fusion and interpolation. The contribution of this work is twofold. First we customize an image registration approach using Scale Invariant Feature Transform (SIFT), Belief Propagation and Random Sampling Consensus (RANSAC) for super-resolution. Second, we propose SVD-based fusion to integrate the important features from the low-resolution images. The proposed image registration and fusion steps effectively maintain the important features and greatly improve the super-resolution results. Results, for a variety of image examples, show that the proposed method successfully generates high-resolution images from low-resolution images.

Item type: Article
ID code: 40246
Keywords: super-resolution, image fusion, high-resolution image, image resolution, Electrical engineering. Electronics Nuclear engineering, Signal Processing, Software, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering
Subjects: Technology > Electrical engineering. Electronics Nuclear engineering
Department: Faculty of Engineering > Electronic and Electrical Engineering
Technology and Innovation Centre > Sensors and Asset Management
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Depositing user: Pure Administrator
Date Deposited: 28 Jun 2012 15:49
Last modified: 27 Mar 2014 09:32
URI: http://strathprints.strath.ac.uk/id/eprint/40246

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