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An advanced computing in fuzzy rule-based preprocessing design of image filters’ system for removing impulse noises

Abstract

In this study, advanced computing in fuzzy rule-based preprocessing classifier is used to categorize five distribution types that are identified as noise by noise detection from the service of next era cloud-empowered computing and techniques. The proposed method extracts useful local information from the corrupted image that is supported by filter processing and resulted in more image details to preserve. The fuzzy rule-based preprocessing classifier goes through a four-phase detection procedure to determine the condition of central pixels for the local image window by using the similarity between the neighboring pixels. A filters’ system is set up with our proposed fuzzy rule-based preprocessing classifier with several effective filters to verify its performance. Simulation results are compared with other individual filters by objective numerical measurements and subjectively visual inspection to indicate that our proposed method performs significantly better in terms of noise suppression and detail preservation.

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Acknowledgements

The authors would like to thank the Editor-in-Chief and Managing Editor of The Journal of Supercomputing and the anonymous Referees for their useful comments and suggestions, which were helpful in improving the presentation and quality of this paper. The author cordially thanks the Ministry of Science and Technology of the Republic of China, Taiwan, for partially financially supporting this research under Contract No. MOST 105-2410-H-146-002.

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Correspondence to You-Shyang Chen.

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Chang, JR., Chen, YS., Lin, HW. et al. An advanced computing in fuzzy rule-based preprocessing design of image filters’ system for removing impulse noises. J Supercomput 73, 3212–3228 (2017). https://doi.org/10.1007/s11227-017-1979-9

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  • DOI: https://doi.org/10.1007/s11227-017-1979-9

Keywords

  • Image processing
  • Impulsive noise
  • Edge preservation
  • Fuzzy classifier