Fuzzy Based Fast Non Local Mean Filter to Denoise Rician Noise

Authors

  • Devinder Singh
  • Amandeep Kaur

Keywords:

• Image denoising • Fuzzy Based Non Local Mean • Rician Noise

Abstract

In    this    paper,     a     new     Fuzzy     based     Fast     Non     Local     Mean     algorithm     is     proposed to denoise Rician   noise   from   MRI   images.   Initially,   Fuzzy   function   used   to   find   the   similar and     non-similar     pixel.     After     this,     Non     Local     Mean(NLM)     algorithm     with      integral image representation is used to find the weights of similar pixel   at   a   faster   rate   than   the normal NLM algorithm in   the   image.   Consequently   these   similar   pixels   are   used   to   generate the   noise   free   pixels.   At   the   end   the    conventional    bias    subtraction    method    is    used    as post processing step. The proposed scheme is tested with real data set and   compared   with existing    Fast    NLM    techniques    and    basic    NLM    using    Root    mean     square     error(RMSE), peak signal   noise ratio (PSNR), Structure similar index (SSIM), quality index and computational time     parameters     methods.     The     proposed     method     gave     better      result     than     existing Fast   NLM   technique   with   high   and    density    Rician    noise    in    the    image    and    it    is    Fast than NLM.

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Published

2021-04-30

How to Cite

Singh, D. ., & Kaur, A. . (2021). Fuzzy Based Fast Non Local Mean Filter to Denoise Rician Noise. The Journal of Contemporary Issues in Business and Government, 27(2), 4572–4588. Retrieved from https://cibgp.com/au/index.php/1323-6903/article/view/1378

Issue

Vol. 27 No. 2 (2021): The journal of contemporary issues in business and government

Section

Articles

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