An efficient algorithm to calculate sample and rank selection probabilities for weighted median filters

Aldo Morales; Eugene Boman; Sung Jea Ko

doi:10.1109/LSP.2002.1009005

An efficient algorithm to calculate sample and rank selection probabilities for weighted median filters

Aldo Morales, Eugene Boman, Sung Jea Ko

School of Science, Engineering & Technology (Harrisburg)

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

Sample and rank selection probabilities are important in the analysis of weighted median filters as well as in comparing linear and nonlinear filters. In this correspondence, we propose a new, efficient algorithm to calculate these probabilities for weighted median filters. The computational savings of this new algorithm are substantial and compare favorably with other known algorithms.

Original language	English (US)
Pages (from-to)	148-150
Number of pages	3
Journal	IEEE Signal Processing Letters
Volume	9
Issue number	5
DOIs	https://doi.org/10.1109/LSP.2002.1009005
State	Published - May 2002

All Science Journal Classification (ASJC) codes

Signal Processing
Electrical and Electronic Engineering
Applied Mathematics

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10.1109/LSP.2002.1009005

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title = "An efficient algorithm to calculate sample and rank selection probabilities for weighted median filters",

abstract = "Sample and rank selection probabilities are important in the analysis of weighted median filters as well as in comparing linear and nonlinear filters. In this correspondence, we propose a new, efficient algorithm to calculate these probabilities for weighted median filters. The computational savings of this new algorithm are substantial and compare favorably with other known algorithms.",

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year = "2002",

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AU - Morales, Aldo

AU - Boman, Eugene

AU - Ko, Sung Jea

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N2 - Sample and rank selection probabilities are important in the analysis of weighted median filters as well as in comparing linear and nonlinear filters. In this correspondence, we propose a new, efficient algorithm to calculate these probabilities for weighted median filters. The computational savings of this new algorithm are substantial and compare favorably with other known algorithms.

AB - Sample and rank selection probabilities are important in the analysis of weighted median filters as well as in comparing linear and nonlinear filters. In this correspondence, we propose a new, efficient algorithm to calculate these probabilities for weighted median filters. The computational savings of this new algorithm are substantial and compare favorably with other known algorithms.

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M3 - Article

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EP - 150

JO - IEEE Signal Processing Letters

JF - IEEE Signal Processing Letters

IS - 5

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An efficient algorithm to calculate sample and rank selection probabilities for weighted median filters

Abstract

All Science Journal Classification (ASJC) codes

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