计算机工程与应用2019，Vol.55Issue(6)：191-196,6.DOI:10.3778/j.issn.1002-8331.1712-0436
利用信息熵的高光谱遥感影像降维方法
Dimensionality Reduction Method for Hyperspectral Remote Sensing Image Based on Informa-tion Entropy
摘要
Abstract
Hyperspectral remote sensing images provide almost continuous spectrum for the surface observation of the earth. However, there are more redundancy information within the bands, which pose challenges to storage, analysis and visualization of the hyperspectral remote sensing images. Thus, dimensionality reduction for hyperspectral remote sensing images become a key step of preprocessing. In this paper, the theory of information entropy is adopted to design the dimensionality reduction method. Each band of hyperspectral remote sensing images are abstracted as independent indi-vidual, and the decision table matrix of hyperspectral remote sensing images are designed, and then the bands are ordered based on the information gain. According to the accuracy requirement of the analysis of hyperspectral remote sensing images, the different bands are selected based on the ordered bands, which are considered as the results of the dimensional-ity reduction. Taking the classification accuracy of remote sensing as an example to evaluate the feasibility and superiority of the dimensionality reduction methods in hyperspectral remote sensing, and based on the experimental results, the pro-posed method has marked advantages and outperformed other methods.关键词
降维方法/信息熵/高光谱遥感影像Key words
dimensionality reduction method/information entropy/hyperspectral remote sensing image分类
信息技术与安全科学引用本文复制引用
黄冬梅,梁素玲,王振华,孙婧琦,徐首珏..利用信息熵的高光谱遥感影像降维方法[J].计算机工程与应用,2019,55(6):191-196,6.基金项目
国家重点研究发展计划(No.2015CB351705) （No.2015CB351705）
国家自然科学基金(No.61402002). （No.61402002）
