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http://dx.doi.org/10.5573/ieek.2013.50.4.144

Super-resolution Algorithm using Local Structure Analysis and Scene Adaptive Dictionary  

Choi, Ik Hyun (School of Electronic Engineering, Inha University)
Lim, Kyoung Won (School of Electronic Engineering, Inha University)
Song, Byung Cheol (School of Electronic Engineering, Inha University)
Publication Information
Journal of the Institute of Electronics and Information Engineers / v.50, no.4, 2013 , pp. 144-154 More about this Journal
Abstract
This paper proposes a new super-resolution algorithm where sharpness enhancement is merged in order to improve overall visual quality of up-scaled images. In the learning stage, multiple dictionaries are generated according to sharpness strength, and a proper dictionary among those dictionaries is selected to adapt to each patch in the inference stage. Also, additional post-processing suppresses boosting of artifacts in input low-resolution images during the inference stage. Experimental results that the proposed algorithm provides 0.3 higher CPBD than the bi-cubic and 0.1 higher CPBD than Song's and Fan's algorithms. Also, we can observe that the proposed algorithm shows better quality in textures and edges than the previous works. Finally, the proposed algorithm has a merit in terms of computational complexity because it requires the memory of only 17% in comparison with the previous work.
Keywords
Super-resolution; Learning; Dictionary; Sharpness enhancement; Region classification;
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Times Cited By KSCI : 1  (Citation Analysis)
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