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http://dx.doi.org/10.5909/JBE.2015.20.5.676

Dictionary Learning based Superresolution on 4D Light Field Images  

Lee, Seung-Jae (Department of Information and Communication Engineering, Inha University)
Park, In Kyu (Department of Information and Communication Engineering, Inha University)
Publication Information
Journal of Broadcast Engineering / v.20, no.5, 2015 , pp. 676-686 More about this Journal
Abstract
A 4D light field image is represented in traditional 2D spatial domain and additional 2D angular domain. The 4D light field has a resolution limitation both in spatial and angular domains since 4D signals are captured by 2D CMOS sensor with limited resolution. In this paper, we propose a dictionary learning-based superresolution algorithm in 4D light field domain to overcome the resolution limitation. The proposed algorithm performs dictionary learning using a large number of extracted 4D light field patches. Then, a high resolution light field image is reconstructed from a low resolution input using the learned dictionary. In this paper, we reconstruct a 4D light field image to have double resolution both in spatial and angular domains. Experimental result shows that the proposed method outperforms the traditional method for the test images captured by a commercial light field camera, i.e. Lytro.
Keywords
Superresolution; dictionary learning; light field; spatial domain; angular domain; Lytro;
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