摘要
不同类型的地物，由于辐射光谱分布不同，在多维光谱空间中构成不同的特征向量，这些向量可以用二进制数码表征．本文介绍的动态聚类方法便是一种基于二进制特征向量的非监督分类方法．
Different types of terrain would lie on the different site in the spectral space,which correspond
to a vector of binary spectral features.The reflecting spectral of terrain could be described
conveniently and exactly with the binary vector presented by Mark.J.Carlotto 1 in 1996.This
vector consists of several binary codes,which result from relative value between bands.In this
paper,a unsupervised clustering algorithm for Landsat thematic mapper based on a vector of
binary spectral features is presented,The algorithm could be used to cluster TM data
successfully compared with K mean clustering algorithm.
出处
《光子学报》
EI
CAS
CSCD
1999年第5期473-477,共5页
Acta Photonica Sinica
关键词
主扫描图象
二进制特征向量
动态聚类
图象
Thematic mapper
Vector of
binary features
Hamming distance
Clustering
