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A random-valued impulse noise removal algorithm with local deviation index and edge-preserving regularization

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Abstract

In this paper, we present a two-phase random-valued impulse noise removal algorithm based on local deviation index (LDI) and edge-preserving regularization. In the first phase, we define an image statistic LDI. Then with image pixels’ LDI values, the outlier candidates are identified. In the second phase, the image is denoised by an edge-preserving regularization method. Extensive experimental results indicate that our method performances better than many existing filters do for its robust image restoration and accurate noise detection.

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Acknowledgments

This work was supported by the National Key Technologies R&D Program of China during the 12th five-year period (2012BAJ23B02).

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Authors and Affiliations

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

    Zhu Zhu, Xueyin Wan & Qing Wang

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

    Xiaoguo Zhang

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  1. Zhu Zhu
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  2. Xiaoguo Zhang
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  3. Xueyin Wan
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  4. Qing Wang
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Correspondence to Qing Wang.

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Zhu, Z., Zhang, X., Wan, X. et al. A random-valued impulse noise removal algorithm with local deviation index and edge-preserving regularization. SIViP 9, 221–228 (2015). https://doi.org/10.1007/s11760-013-0426-5

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  • DOI: https://doi.org/10.1007/s11760-013-0426-5

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