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Design of a highly effective multi-layered fuzzy logic based image enhancement filter
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| 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.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.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.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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6th International Symposium - 2016 [126]
This is the proceedings of 6th International Symposium held on 20 -21 December, 2016 at the South Eastern University of Sri Lanka