Design of a highly effective multi-layered fuzzy logic based image enhancement filter

dc.contributor.author	Anver, M.M.
dc.date.accessioned	2016-12-21T12:50:07Z
dc.date.available	2016-12-21T12:50:07Z
dc.date.issued	2016-12-20
dc.description.abstract	This paper describes the development of an effective fuzzy image filter which consists of a multi-layered fuzzy structure for the removal of noise from images heavily corrupted by impulse noise, while preserving the intricate details of the image. The introduction of multi-layered fuzzy systems substantially decreases the number of rules to be learnt. We then show how Evolutionary Algorithms (EAs) can be used to effectively learn the fuzzy rules in each knowledge base. Results are presented for impulse noise corruption of the well-known ‘Lena’ image.	en_US
dc.identifier.citation	6th International Symposium 2016 on “Multidisciplinary Research for Sustainable Development in the Information Era,” pp 235-243.	en_US
dc.identifier.isbn	978-955-627-098-3
dc.identifier.uri	http://ir.lib.seu.ac.lk/handle/123456789/1955
dc.language.iso	en_US	en_US
dc.publisher	South Eastern University of Sri Lanka	en_US
dc.subject	Fuzzy filter	en_US
dc.subject	image enhancement	en_US
dc.subject	Multilayered fuzzy system	en_US
dc.subject	Evolutionary learning	en_US
dc.subject	Evolutionary algorithm.	en_US
dc.title	Design of a highly effective multi-layered fuzzy logic based image enhancement filter	en_US
dc.type	Article	en_US

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