Adaptive image noise filtering using transform domain local statistics

Steven S.O. Choy, Yuk Hee Chan, Wan Chi Siu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

11 Citations (Scopus)


Image noise filtering has been widely perceived as an estimation problem in the spatial domain. We deal with it as an estimation problem in an uncorrelated transform domain. This idea leads to a generalization of the adaptive linear minimum mean square error (LMMSE) estimator for filtering noisy images. In our proposed method, the transform-domain local statistics obtained from the noisy image are exploited. Due to the fact that the transform-domain local statistics carry more information about the image than the spatial-domain local statistics do, improvement in noise filtering is gained overall and is particularly Significant in the Vicinity of edges.
Original languageEnglish
Pages (from-to)2290-2296
Number of pages7
JournalOptical Engineering
Issue number8
Publication statusPublished - 1 Jan 1998


  • Adaptive linear minimum mean square error estimation
  • Decorrelation
  • Image noise smoothing
  • Image restoration
  • Local statistics

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Engineering(all)

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