吉林大学学报(理学版)

• 计算机科学 • 上一篇    下一篇

一种基于图像熵的密度峰值聚类波段选择方法

赵海士, 路来君, 杨晨   

  1. 吉林大学 地球科学学院, 长春 130061
  • 收稿日期:2016-11-25 出版日期:2017-03-26 发布日期:2017-03-24
  • 通讯作者: 杨晨 E-mail:yangc616@jlu.edu.cn

A Method for Density Peaks Clustering BandSelection Based on Image Entropy

ZHAO Haishi, LU Laijun, YANG Chen   

  1. College of Earth Sciences, Jilin University, Changchun 130061, China
  • Received:2016-11-25 Online:2017-03-26 Published:2017-03-24
  • Contact: YANG Chen E-mail:yangc616@jlu.edu.cn

摘要: 基于将图像熵引入到密度峰值聚类算法中以确定波段信息量, 提出一种基于图像熵的密度峰值聚类波段选择方法. 通过构建衡量波段重要性得分, 解决了传统密度峰值聚类方法在波段选择时未考虑波段信息量的问题. 实验结果表明, 该方法的分类精度较传统密度峰值聚类方法平均提高2.12%.

关键词: 密度峰值聚类, 波段选择, 高光谱遥感, 图像熵

Abstract: Based on the introduction of image entropy into the den sity peaks clustering algorithm to determine the information quantity of spectra l band, we proposed a method for density peaks clustering band selection based o n image entropy. By constructing the measuring score of bands signif icance, we solved the problem of the band selection in the traditional density peaks clustering method without considering the info rmation quantity of the bands. The experiment al results show that the classification accuracy of the proposed method increase s by an average of 2.12% than that of the traditional density peaks clustering method.

Key words: band selection (BS), hyperspectral remote sensing, density peak clustering (DPC), image entropy

中图分类号: 

  • TP751