Nonlinear filtering by threshold decomposition

Jean Hsang Lin, Nirwan Ansari, Jinhui Li

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

A new threshold decomposition architecture is introduced to implement stack filters. The architecture is also generalized to a new class of nonlinear filters known as threshold decomposition (TD) filters which are shown to be equivalent to the class of Ll-filters under certain conditions. Another new class of filters known as linear and order-statistic (LOS) filters result from the intersection of the class of TD and Ll-filters. Performance comparison among several filters are then presented. It was found that TD is compatible with Ll, LOS, and linear filters in suppressing Gaussian noise, and is superior in suppressing salt-and-pepper noise. LOS filters, however, provide a better compromise in performance and complexity.

Original languageEnglish (US)
Pages (from-to)925-933
Number of pages9
JournalIEEE Transactions on Image Processing
Volume8
Issue number7
DOIs
StatePublished - 1999

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Graphics and Computer-Aided Design

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