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http://dx.doi.org/10.5909/JBE.2016.21.2.180

Super-resolution Algorithm Using Adaptive Unsharp Masking for Infra-red Images  

Kim, Yong-Jun (Department of Electronic Engineering, Inha University)
Song, Byung Cheol (Department of Electronic Engineering, Inha University)
Publication Information
Journal of Broadcast Engineering / v.21, no.2, 2016 , pp. 180-191 More about this Journal
Abstract
When up-scaling algorithms for visible light images are applied to infrared (IR) images, they rarely work because IR images are usually blurred. In order to solve such a problem, this paper proposes an up-scaling algorithm for IR images. We employ adaptive dynamic range encoding (ADRC) as a simple classifier based on the observation that IR images have weak details. Also, since human visual systems are more sensitive to edges, our algorithm focuses on edges. Then, we add pre-processing in learning phase. As a result, we can improve visibility of IR images without increasing computational cost. Comparing with Anchored neighborhood regression (A+), the proposed algorithm provides better results. In terms of just noticeable blur, the proposed algorithm shows higher values by 0.0201 than the A+, respectively.
Keywords
Super-Resolution; Infrared image; Edge enhancement;
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Times Cited By KSCI : 1  (Citation Analysis)
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