Clustering multispectral images: a tutorial

被引：61

作者：

Tran, TN ^{[1
]}

Wehrens, R ^{[1
]}

Buydens, LMC ^{[1
]}

机构：

[1] Univ Nijmegen, Analyt Chem Lab, NSRIM Res Sch, NL-6525 ED Nijmegen, Netherlands

来源：

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS | 2005年 / 77卷 / 1-2期

关键词：

pattern recognition; unsupervised classification;

D O I：

10.1016/j.chemolab.2004.07.011

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A huge number of clustering methods have been applied to many different kinds of data set including multivariate images, such as magnetic resonance images (MRI) and remote sensing images. However, not many methods include spatial information of the image data. In this tutorial, the major types of clustering techniques are summarized. Particular attention will be devoted to the extension of clustering techniques to take into account both spectral and spatial information of the multivariate image data. General guidelines for the optimal use of these algorithms are given. The application of pre- and post-processing methods is also discussed. (c) 2004 Elsevier B.V All rights reserved.

引用

页码：3 / 17

页数：15

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