Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/95919
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Type: Journal article
Title: A fuzzy-rule-based approach for single frame super resolution
Author: Purkait, P.
Pal, N.
Chanda, B.
Citation: IEEE Transactions on Image Processing, 2014; 23(5):2277-2290
Publisher: IEEE
Issue Date: 2014
ISSN: 1057-7149
1941-0042
Statement of
Responsibility: 
Pulak Purkait, Nikhil Ranjan Pal and Bhabatosh Chanda
Abstract: In this paper, a novel fuzzy rule-based prediction framework is developed for high-quality image zooming. In classical interpolation-based image zooming, resolution is increased by inserting pixels using certain interpolation techniques. Here,we propose a patch-based image zooming technique, where each low-resolution (LR) image patch is replaced by an estimated high-resolution (HR) patch. Since an LR patch can be generated from any of the many possible HR patches, it would be natural to develop rules to find different possible HR patches and then to combine them according to rule strength to get the estimated HR patch. Here, we generate a large number of LR–HR patch pairs from a collection of natural images, group them into different clusters, and then generate a fuzzy rule for each of these clusters. The rule parameters are also learned from these LR-HR patch pairs. As a result, an efficient mapping from LR patch space to HR patch space can be formulated. The performance of the proposed method is tested on different images,and is also compared with other representative as well as state-of-the-art image zooming techniques. Experimental results show that the proposed method is better than the competing methods and is capable of reconstructing thin lines, edges, fine details, and textures in the image efficiently.
Keywords: Super resolution; image zooming; LR-HR patch pairs; fuzzy rules; Takagi-Sugeno model; Gaussian mixture model.
Rights: © 2014 IEEE.
DOI: 10.1109/TIP.2014.2312289
Appears in Collections:Aurora harvest 7
Electrical and Electronic Engineering publications

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