Multicriteria Approach to 2D Image De-Noising by Means of Lukasiewicz Algebra with Square Root

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22340%2F02%3A00007057" target="_blank" >RIV/60461373:22340/02:00007057 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Multicriteria Approach to 2D Image De-Noising by Means of Lukasiewicz Algebra with Square Root

Original language description

The image de-noising is a practical application of image processing. Both linear and nonlinear filters are used for the noise reduction. The filters, which are realizable in Lukasiewicz algebra with square root, were analyzed first and then they were used for the 2D image de-noising. There is a set of quality measures recommended for the evaluation of de-noising quality. In case of various quality measures we can find the best filter. The Pareto optimality principle and the AIA technique were used for this purpose. The procedures were demonstrated on a set of MRI biomedical images.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

JD - Use of computers, robotics and its application

OECD FORD branch

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Project

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Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2002

Confidentiality

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

Name of the periodical

Neural Network World

ISSN

1210-0552

e-ISSN

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Volume of the periodical

12

Issue of the periodical within the volume

4

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

16

Pages from-to

333-348

UT code for WoS article

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EID of the result in the Scopus database

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