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

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Abstract

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.

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References

  1. S. Akkoul, R. Lédée, R. Leconge, R. Harba, A new adaptive switching median filter. IEEE Signal Process. Lett. 17(6), 587–590 (2010)

    Article  Google Scholar 

  2. A.S. Awad, Standard deviation for obtaining the optimal direction in removal of impulse noise. IEEE Signal Process. Lett. 18(7), 407–410 (2011)

    Article  Google Scholar 

  3. J.F. Cai, R.H. Chan, B. Morini, Minimization of a detail-preserving regularization functional for impulse noise removal. J. Math. Imaging Vis. 29(1), 79–91 (2007)

    Article  Google Scholar 

  4. T. Chen, H.R. Wu, Adaptive impulse detection using center-weighted median filters. IEEE Signal Process. Lett. 8(1), 1–3 (2001)

    Article  Google Scholar 

  5. Y. Dong, R.H. Chan, S. Xu, A detection statistic for random-valued impulse noise. IEEE Trans. Image Process. 16(4), 1112–1120 (2007)

    Article  MathSciNet  Google Scholar 

  6. Y. Dong, S. Xu, A new directional weighted median filter for removal of random-valued impulse noise. IEEE Signal Process. Lett. 14(3), 193–196 (2007)

    Article  Google Scholar 

  7. R. Garnett, T. Huegerich, C. Chui, W. He, A universal noise removal algorithm with an impulse detector. IEEE Trans. Image Process. 14(11), 1747–1754 (2005)

    Article  Google Scholar 

  8. U. Ghanekar, A.K. Singh, R. Pandey, The contrast enhancement-based filter for removal of random valued impulse noise. IEEE Signal Process. Lett. 17(1), 47–50 (2010)

    Article  Google Scholar 

  9. R.C. Gonzalez, R.E. Woods, Digital Image Processing (Prentice-Hall, Englewood Cliffs, 2002)

    Google Scholar 

  10. W. Luo, A new efficient impulse detection algorithm for the removal of impulse noise. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 88-A(10), 2579–2586 (2005)

    Article  Google Scholar 

  11. M. Nikolova, A variational approach to remove outliers and impulse noise. J. Math. Imaging Vis. 20(1–2), 99–120 (2004)

    Article  MathSciNet  Google Scholar 

  12. P.J. Rousseeuw, C. Croux, Alternatives to the median absolute deviation. J. Am. Stat. Assoc. 88(424), 1273–1283 (1993)

    Article  MATH  MathSciNet  Google Scholar 

  13. P. Sun, S. Chawla, SLOM: a new measure for local spatial outlier. Knowl. Inf. Syst. 9(4), 412–429 (2006)

    Article  Google Scholar 

  14. X. Zeng, L. Yang, Mixed impulse and Gaussian noise removal using detail-preserving regularization. Opt. Eng. 49(9), 097002 (2010)

    Article  Google Scholar 

Download references

Acknowledgements

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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Authors and Affiliations

  1. School of Instrument Science and Engineering, Southeast University, Nanjing, 210096, China

    Zhu Zhu, Qing Wang, Xueyin Wan & Yanchang Xiao

  2. Suzhou Research Institute, Southeast University, Suzhou, 215123, China

    Xiaoguo Zhang

Authors
  1. Zhu Zhu
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  2. Xiaoguo Zhang
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  3. Qing Wang
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  4. Xueyin Wan
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  5. Yanchang Xiao
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Correspondence to Zhu Zhu.

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Zhu, Z., Zhang, X., Wang, Q. et al. Edge-Preserving Regularized Filter with Spatial Local Outlier Measure and Q-Estimate. Circuits Syst Signal Process 33, 629–642 (2014). https://doi.org/10.1007/s00034-013-9644-x

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  • DOI: https://doi.org/10.1007/s00034-013-9644-x

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