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Dictionary Learning based Superresolution on 4D Light Field Images
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  • Journal title : Journal of Broadcast Engineering
  • Volume 20, Issue 5,  2015, pp.676-686
  • Publisher : The Korean Institute of Broadcast and Media Engineers
  • DOI : 10.5909/JBE.2015.20.5.676
 Title & Authors
Dictionary Learning based Superresolution on 4D Light Field Images
Lee, Seung-Jae; Park, In Kyu;
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 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;
 Language
Korean
 Cited by
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