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A multi-layered fuzzy image filter for removing impulse noise

Version 2 2022-03-24, 23:50
Version 1 2017-12-06, 00:00
conference contribution
posted on 2022-03-24, 23:50 authored by Russel Stonier, Mohamed AnverMohamed Anver
In this paper we examine how different multi-layered fuzzy structures can be developed as fuzzy image filters for the removal of noise from images heavily corrupted by impulse noise, while preserving the intricate details of the image. Evolutionary Algorithms (EAs) are used to effectively learn the fuzzy rules in each knowledge base. Results are presented for impulse noise corruption of the well-known 'Lena' image.

Funding

Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)

History

Editor

Elmaghraby, AS & Dees, R

Start Page

221

End Page

226

Number of Pages

6

Start Date

2002-07-18

Finish Date

2002-07-20

ISBN-10

1880843439

Location

Boston, Massachusettes

Publisher

ISCA

Place of Publication

Boston

Peer Reviewed

  • Yes

Open Access

  • No

External Author Affiliations

Faculty of Informatics and Communication;

Era Eligible

  • Yes

Name of Conference

International Society for Computers and their Applications. International Conference.

Parent Title

Intelligent systems: Proceedings of the ISCA 11th International Conference

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    Categories

    Keywords

    Image filtersEvolutionary algorithms (EAs)'Lena' imageMulti-layered fuzzy structuresNeural, Evolutionary and Fuzzy Computation

    Licence

    CQUniversity General 1.0

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