Complex-fuzzy adaptive image restoration - An artificial-bee-colony-based learning approach

Chunshien Li, Fengtse Chan

研究成果: 書貢獻/報告類型會議論文篇章同行評審

22 引文 斯高帕斯(Scopus)

摘要

A complex-fuzzy approach using complex fuzzy sets is proposed in the paper to deal with the problem of adaptive image noise cancelling. A image may be corrupted by noise, resulting in the degradation of valuable image information. Complex fuzzy set (CFS) is in contrast with traditional fuzzy set in membership description. A CFS has the membership state within the complexvalued unit disc of the complex plane. Based on the membership property of CFS, we design a complex neural fuzzy system (CNFS), so that the functional mapping ability by the CNFS can be augmented. A hybrid learning method is devised for training of the proposed CNFS, including the artificial bee colony (ABC) method and the recursive least square estimator (RLSE) algorithm. Two cases for image restoration are used to test the proposed approach. Experimental results are shown with good restoration quality.

原文???core.languages.en_GB???
主出版物標題Intelligent Information and Database Systems - Third International Conference, ACIIDS 2011, Proceedings
頁面90-99
頁數10
版本PART 2
DOIs
出版狀態已出版 - 2011
事件3rd International Conference on Intelligent Information and Database Systems, ACIIDS 2011 - Daegu, Korea, Republic of
持續時間: 20 4月 201122 4月 2011

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
號碼PART 2
6592 LNAI
ISSN(列印)0302-9743
ISSN(電子)1611-3349

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???event.eventtypes.event.conference???3rd International Conference on Intelligent Information and Database Systems, ACIIDS 2011
國家/地區Korea, Republic of
城市Daegu
期間20/04/1122/04/11

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