Reducing spatially varying out-of-focus blur from natural image

Faming Fang, Fang Li, Tieyong ZENG*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

In this paper, we focus on the challenging problem of removing the spatially varying out-of-focus blur from a single natural image. We first propose an effective method to estimate the blur map by the total variation refinement on Hölder coefficient, then discuss the properties of the corresponding kernel matrix. A tight-frame based energy functional, whose minimizer is related to the optimal defocus result, is thus built. For tackling functional more efficiently, we describe the numerical procedure based on an accelerated primal-dual scheme. To verify the effectiveness of our method, we compare it with some state-of-the-art schemes using both synthesized and natural images. Experimental results demonstrate that the proposed method performs better than the compared methods.

Original languageEnglish
Pages (from-to)65-85
Number of pages21
JournalInverse Problems and Imaging
Volume11
Issue number1
DOIs
Publication statusPublished - Feb 2017

Scopus Subject Areas

  • Analysis
  • Modelling and Simulation
  • Discrete Mathematics and Combinatorics
  • Control and Optimization

User-Defined Keywords

  • Blur map
  • Debluring
  • Framelet
  • Out-of-focus
  • Spatially-varying
  • Variational method

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