Feasibility of newly designed fast non local means (FNLM)-based noise reduction filter for X-ray imaging: A simulation study

Jina Shim, Myonggeun Yoon, Youngjin Lee

Research output: Contribution to journalArticle

5 Citations (Scopus)


In the diagnostic radiology field, reducing the radiation dose for patient lead to increased noise in image. Since increases of noise decrease the diagnosis rate, to reduce the noise is necessary. In this study quantitatively evaluates the four widely used and newly verified filters which remove noise in image: median, Wiener, total variation, and fast non local means (FNLM). For that purpose, X-ray and computed tomography (CT) images are acquired using MATLAB simulation with 3D voxelized phantom. To evaluate image performance, normalized noise power spectrum (NNPS), contrast to noise ratio (CNR) and coefficient of variation (COV) were used. As a result, we can efficiently remove noise in X-ray image when FNLM filter was used compared with frequently used filters. In conclusion, our results demonstrated that our proposed FNLM filter shows superior denoising performance, which is expected to enhance the detection of diseases in clinical images with low dose.

Original languageEnglish
Pages (from-to)124-130
Number of pages7
Publication statusPublished - 2018 May 1



  • Fast non local means (FNLM) filter
  • Image performance evaluation
  • Median filter
  • Simulation study
  • Total variation (TV) filter
  • Wiener filter

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Electrical and Electronic Engineering

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