文献类型：期刊文献

英文题名：An adaptive weighted fuzzy C-means clustering algorithm for remote sensing image classification

作者：Liu, Wenping[1]; Cui, Tianyi[1]; Hung, Chih-Cheng[2]; Chen, Shihong[3]

第一作者：Liu, Wenping

通讯作者：Liu, W.

机构：[1] Institute of Information, Beijing Forestry University, Beijing 100083, China; [2] National Anyang University, China and Southern Polytechnic State University, United States; [3] College of Arts and Science, Beijing Union University, Beijing 102200, China

第一机构：Institute of Information, Beijing Forestry University, Beijing 100083, China

年份：2013

卷号：10

期号：7

起止页码：2009-2020

外文期刊名：Journal of Information and Computational Science

收录：EI(收录号：20132316396459);Scopus(收录号：2-s2.0-84878353975)

语种：英文

外文关键词：Clustering algorithms - Fuzzy clustering - Fuzzy systems - Image analysis - Image reconstruction - Mobile telecommunication systems

摘要：The Fuzzy C-means (FCM) clustering algorithm is a well-known tool for pattern and image classification, while FCM is showing unstable behaviors with different fuzzy indexes. The New Weighted Fuzzy C-means (NW-FCM) algorithm, based on the weighted mean concept, was proposed to improve the performance of FCM, however, NW-FCM needs man-machine interaction and can not classify by itself. In this paper, an Adaptive Weighted Fuzzy Clustering Algorithm (AWFCM), which integrates the weighted mean concept with the mechanism of splitting and lumping from the Iterative Self-organizing Data Analysis Techniques Algorithm (ISODATA), is proposed for remote sensing image classification. At the same time, a statistical method is introduced into the algorithm. The AWFCM does not need a priori knowledge about the number of clusters and their centers, and can automatically estimate an initial number of clusters and their centers, also the optimum final number of clusters. Experimental results demonstrate that the AWFCM has better performance than those of the K-means, ISODATA and FCM algorithms. ? 2013 by Binary Information Press.