articleJun 1, 2013Closed access

Unnatural L0 Sparse Representation for Natural Image Deblurring

Chinese University of Hong Kong

Indexed incrossref

Abstract

We show in this paper that the success of previous maximum a posterior (MAP) based blur removal methods partly stems from their respective intermediate steps, which implicitly or explicitly create an unnatural representation containing salient image structures. We propose a generalized and mathematically sound L 0 sparse expression, together with a new effective method, for motion deblurring. Our system does not require extra filtering during optimization and demonstrates fast energy decreasing, making a small number of iterations enough for convergence. It also provides a unified framework for both uniform and non-uniform motion deblurring. We extensively validate our method and show comparison with other…

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1,114
total citations
FWCI
53.03
Percentile
100%
References
38
Citations per year

Authors

3

Topics & keywords

Keywords
  • Deblurring
  • Convergence (economics)
  • Representation (politics)
  • Computer science
  • Image (mathematics)
  • Salient
  • Motion blur
  • Sparse approximation
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