Circuits, Systems, and Signal Processing

, Volume 33, Issue 2, pp 629–642 | Cite as

Edge-Preserving Regularized Filter with Spatial Local Outlier Measure and Q-Estimate

  • Zhu Zhu
  • Xiaoguo Zhang
  • Qing Wang
  • Xueyin Wan
  • Yanchang Xiao
Short Paper


This paper presents an efficient random-valued impulse noise removal algorithm. The filtering process contains two phases: a detection phase followed by a filtering phase. In the detection phase, the proposed method uses the novel image statistics, the spatial local outlier measure (SLOM) and the Q-estimate, to identify impulses in a corrupted image. When the noise pixels are identified, their values are restored by an edge-preserving regularized method in the filtering phase. Extensive experimental results show that our filter provides a significant improvement over many other existing techniques.


Random-valued impulse noise Spatial local outlier measure Q-Estimate Edge-preserving regularized method 



The authors acknowledge the support of The National Key Technologies R&D Program of China during the 12th Five-Year Period (No. 2012BAJ23B02).


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Zhu Zhu
    • 1
  • Xiaoguo Zhang
    • 2
  • Qing Wang
    • 1
  • Xueyin Wan
    • 1
  • Yanchang Xiao
    • 1
  1. 1.School of Instrument Science and EngineeringSoutheast UniversityNanjingChina
  2. 2.Suzhou Research InstituteSoutheast UniversitySuzhouChina

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