Interval Type-2 enhanced possibilistic fuzzy C-means noisy image segmentation algorithm amalgamating weighted local information

The fuzzy clustering algorithms based on interval type-2 are effective methods for data clustering and image segmentation with some potential advantages in dealing with higher-order uncertainty. However, the fuzzy clustering algorithms based on interval type-2 have limited accuracy in noisy image se...

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Vydáno v:	Engineering applications of artificial intelligence Ročník 137; s. 109135
Hlavní autoři:	Huang, Chengquan, Lei, Huan, Chen, Yang, Cai, Jianghai, Qin, Xiaosu, Peng, Jialei, Zhou, Lihua, Zheng, Lan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 01.11.2024
Témata:	Interval type-2 possibilistic fuzzy C-Means Local features Noisy image Weighted local information Weighted sum function Weighted local information Interval type-2 possibilistic fuzzy C-Means Local features Weighted sum function Noisy image
ISSN:	0952-1976
On-line přístup:	Získat plný text
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