Optimum Filtering as Multicriteria Decision Making Task

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Optimum Filtering as Multicriteria Decision Making Task

Popis výsledku v původním jazyce

Filtering quality can be estimated on various data sets by various measures. Five basic quality measures were used: mean square of error (MSE), mean of absolute error (MAE), maximum of absolute error (MAX), median of absolute error (MED) and signal to noise ratio (SNR). Then the quality of given filter is not a scalar but it is a vector of various measures on various data sets. The testing results of various filters can be collected to quality matrix. There is a possibility to find optimum filter usingmulticriteria decision-making technique. Finding ideal and basic alternatives is the first step. The quality matrix normalization is the second step. The last step is based on no a priori knowledge of quality measure weights and we use AIA technique forthe best filter selection. The resulting optimum filter guarantees compromise quality of various data set processing. The general principle is demonstrated on 2D MRI image de-noising.

Název v anglickém jazyce

Optimum Filtering as Multicriteria Decision Making Task

Popis výsledku anglicky

Filtering quality can be estimated on various data sets by various measures. Five basic quality measures were used: mean square of error (MSE), mean of absolute error (MAE), maximum of absolute error (MAX), median of absolute error (MED) and signal to noise ratio (SNR). Then the quality of given filter is not a scalar but it is a vector of various measures on various data sets. The testing results of various filters can be collected to quality matrix. There is a possibility to find optimum filter usingmulticriteria decision-making technique. Finding ideal and basic alternatives is the first step. The quality matrix normalization is the second step. The last step is based on no a priori knowledge of quality measure weights and we use AIA technique forthe best filter selection. The resulting optimum filter guarantees compromise quality of various data set processing. The general principle is demonstrated on 2D MRI image de-noising.

Druh

D - Stať ve sborníku

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2002

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proc. of the 5th Int. Scientific - Technical Conference on Process Control '02

ISBN

80-7194-452-1

ISSN

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e-ISSN

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Počet stran výsledku

8

Strana od-do

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Název nakladatele

University of Pardubice

Místo vydání

Pardubice

Místo konání akce

Kouty nad Desnou

Datum konání akce

9. 6. 2002

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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