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Fuzzy Logic-Based Filter for Removing Additive and Impulsive Noise from Color Images

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Abstract

This paper presents an efficient filter method based on fuzzy logics for adaptively removing additive and impulsive noise from color images. The proposed filter comprises two parts including noise detection and noise removal filtering. In the detection part, the fuzzy peer group concept is applied to determine what type of noise is added to each pixel of the corrupted image. In the filter part, the impulse noise is deducted by the vector median filter in the CIELAB color space and an optimal fuzzy filter is introduced to reduce the Gaussian noise, while they can work together to remove the mixed Gaussian-impulse noise from color images. Experimental results on several color images proves the efficacy of the proposed fuzzy filter.

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Acknowledgements

The authors would like to thank Prof Y. Wei and Prof S. Wang for spending hours in discussion with us and patiently reviewing this paper. The authors would also like to thank Dr. Y. Xu and Dr. Z. Li for offering useful suggestions and information to improve the presentation of the paper. The first author H. Jiang has done much in editing this paper and finishing the program work for the experiments. The second author Y. Zhu has provided lots of useful material and information, while improving the technical content of the paper by his valuable comments and suggestions.

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Authors and Affiliations

  1. Communication Engineering, Lab 517, Jilin University, No. 5372 Nanhudalu, Changchun, 130012, China

    Yuhong Zhu, Hongyang Li & Huageng Jiang

Authors
  1. Yuhong Zhu
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  2. Hongyang Li
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  3. Huageng Jiang
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Correspondence to Huageng Jiang.

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Zhu, Y., Li, H. & Jiang, H. Fuzzy Logic-Based Filter for Removing Additive and Impulsive Noise from Color Images. Sens Imaging 18, 3 (2017). https://doi.org/10.1007/s11220-016-0150-7

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  • DOI: https://doi.org/10.1007/s11220-016-0150-7

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