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Intelligent noise detection and filtering using neuro-fuzzy system

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Abstract

In this paper, we propose a neuro-fuzzy based blind image restoration to remove impulse noise from low as well as highly corrupted images. Main components of the proposed technique include noise detection, histogram estimation and noise filtering process. Proposed technique constructs the fuzzy sets using fuzzy number construction algorithm. These fuzzy sets are used in noise filtering process to remove impulse noise from the noisy pixels using neuro-fuzzy inference system and fuzzy decider. Experimental results are based on global and local error measures, which prove that the proposed technique gives superior results than the present well known impulse noise filtering methods.

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Acknowledgement

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MEST) (No. 2011–0006644).

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Authors and Affiliations

  1. National University of Computer & Emerging Sciences, Islamabad, Pakistan

    Sohail Masood & M. Arfan Jaffar

  2. International Islamic University, Islamabad, Pakistan

    Ayyaz Hussain

  3. Gwangju Institute of Science & Technology, Gwangju, South Korea

    M. Arfan Jaffar & Tae-Sun Choi

Authors
  1. Sohail Masood
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  2. Ayyaz Hussain
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  3. M. Arfan Jaffar
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  4. Tae-Sun Choi
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Corresponding author

Correspondence to M. Arfan Jaffar.

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Masood, S., Hussain, A., Jaffar, M.A. et al. Intelligent noise detection and filtering using neuro-fuzzy system. Multimed Tools Appl 63, 93–105 (2013). https://doi.org/10.1007/s11042-012-1015-2

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  • DOI: https://doi.org/10.1007/s11042-012-1015-2

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