Multivariate self-dual morphological operators

Tao Lei, Yangyu Fan, Zhe Guo, Feng Wei, Weihua Liu

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Self-dual morphological operators (SDMO) do not rely on whether one starts the sequence with erosion or dilation, they treat the image foreground and background identically. Nevertheless, it is difficult to extend SDMO to multi-channel images. Based on the self-duality property of traditional morphological operators and the theory of extremum constraint, this paper gives a complete characterization for the construction of multivariate SDMO. We introduce a pair of symmetric vector orderings (SVO) to construct multivariate dual morphological operators. Utilizing extremum constraint to optimize multivariate morphological operators, we further establish methods for the construction of multivariate SDMO. Finally, we illustrate the importance and effectiveness of the multivariate SDMO by an application of noise removal in color images. The experimental results show that the proposed multivariate SDMO provide better results, they can suppress noises efficiently while maintaining image details compared with other operators.

源语言英语
主期刊名2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings
出版商Institute of Electrical and Electronics Engineers Inc.
359-363
页数5
ISBN(电子版)9781479954032
DOI
出版状态已出版 - 3 9月 2014
活动2nd IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Xi'an, 中国
期限: 9 7月 201413 7月 2014

出版系列

姓名2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings

会议

会议2nd IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014
国家/地区中国
Xi'an
时期9/07/1413/07/14

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