A New Weighted Fuzzy C-Means Clustering Algorithm for Remotely Sensed Image Classification

Fuzzy clustering model is an essential tool to find the proper cluster structure of given data sets in pattern and image classification. In this paper, a new weighted fuzzy C-Means (NW-FCM) algorithm is proposed to improve the performance of both FCM and FWCM models for high-dimensional multiclass p...

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Veröffentlicht in:	IEEE journal of selected topics in signal processing Jg. 5; H. 3; S. 543 - 553
Hauptverfasser:	Chih-Cheng Hung, Kulkarni, S, Bor-Chen Kuo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.06.2011 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accuracy Algorithm design and analysis Algorithms Classification algorithms Clustering Clustering algorithms Clusters Discriminant analysis feature extraction (DAFE) Feature extraction Fuzzy fuzzy C-means algorithm (FCM) Fuzzy logic Fuzzy set theory fuzzy weighted C-means algorithm (FWCM) nonparametric weighted feature extraction (NWFE) Pattern recognition Principal component analysis Studies
ISSN:	1932-4553, 1941-0484
Online-Zugang:	Volltext
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