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Adaptive non-local means denoising algorithm for Cone-Beam Computed Tomography projection images

  • Northwestern Polytechnical University Xian

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Aiming at the difficulty of choosing filtering parameters of Non-Local Means (NLM) denoising algorithm for Cone-Beam Computed Tomography (CBCT) projection images, an adaptive NLM denoising algorithm is proposed. First, a simplified noise estimation method based on subblock division is proposed to replace the approach of designating the background region, which can adaptively identify the background region and estimate the noise level when the background region is changed obviously. And then an algorithm of adaptively obtaining filter strengths of projection images is proposed by analyzing the impact of filter strength to filtering result in NLM denoising algorithm, in which the filter strength is adjusted according to the characteristics of current image and the noises in all projection images are suppressed to a similar level. The experimental result shows that the proposed algorithm can accurately estimate the noise level of projection image and markedly improve the slice image quality.

Original languageEnglish
Title of host publicationProceedings of the 5th International Conference on Image and Graphics, ICIG 2009
PublisherIEEE Computer Society
Pages33-38
Number of pages6
ISBN (Print)9780769538839
DOIs
StatePublished - 2009
Event5th International Conference on Image and Graphics, ICIG 2009 - Xi'an, Shanxi, China
Duration: 20 Sep 200923 Sep 2009

Publication series

NameProceedings of the 5th International Conference on Image and Graphics, ICIG 2009

Conference

Conference5th International Conference on Image and Graphics, ICIG 2009
Country/TerritoryChina
CityXi'an, Shanxi
Period20/09/0923/09/09

Keywords

  • Cone-Beam Computed Tomography
  • Filter strength
  • Noise estimation
  • Non-local means

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