摘要
提出一种基于最大信息量的高光谱遥感图像无监督波段选择方法.该方法以在所选择的波段中保留原数据中所包含的最大信息量为目标,并采用逐个移除波段的方式来实现.算法使用K-L散度来定量表示信息量的大小,并通过信息量在整个数据集中的分布情况来决定所移除的波段.与传统方法相比,具有物理意义明确、计算过程简单的优点,同时还能够完全自动地完成任务,实现无监督的波段选择.
An unsupervised band selection algorithm for hyperspectral imagery based on maximal information is proposed in this paper.The objective of the method is to preserve the maximal information from original data in the selected bands.The bands with less information are removed one by one from the original data.K-L divergence is used to quantify the information amount and its distribution over all the dataset is considered to judge the specific band which needs to be removed.Compared with traditional methods,the proposed approach has an explicit physical meaning and its computational process is very simple.It is an unsupervised method and can perform automatically.
出处
《红外与毫米波学报》
SCIE
EI
CAS
CSCD
北大核心
2012年第2期166-170,176,共6页
Journal of Infrared and Millimeter Waves
基金
国家自然科学基金(61071134)
863国家高技术研究计划(2009AA12Z115)~~
关键词
高光谱遥感图像
波段选择
信息量
K-L散度
分类
hyperspectral imagery
band selection
information amount
K-L divergence
classification
