Optimal and adaptive design of logical granulometric filters

Edward R. Dougherty, Yidong Chen

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Statistical design of filters for sieving granular random sets that consists of a union of disjoint compact grains are discussed. There is a signal random set S and a noise random set N. Both signal and noise are composed of disjoint grains, and signal and noise are disjoint. Granulometries, as applied to random sets, are based on the morphological opening operator. Given an input set and a structuring element (probe), which is a deterministic set, a point is in the output of the opening if and only if there exists a translate of the structuring element that contains the point and is also a subset of the input set. Points that do not satisfy this structural criterion are removed from the set. Single-parameter granulometric filters formed as unions of reconstructive openings, multiple-parameter granulometric filters formed as unions of reconstructive openings, single-parameter reconstructive granulometric bandpass filters formed as unions of differences of granulometric filters, and logical structural filters (LSFs), are studied.

Original languageEnglish (US)
Pages (from-to)1-71
Number of pages71
JournalAdvances in Imaging and Electron Physics
Volume117
Issue numberC
DOIs
StatePublished - 2001
Externally publishedYes

ASJC Scopus subject areas

  • Nuclear and High Energy Physics
  • Condensed Matter Physics
  • Electrical and Electronic Engineering

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