Information content of multi-angular remote sensing data

被引：0
|
作者：
Xu, WL [1 ]
Yang, H [1 ]
Li, XM [1 ]
Wang, JD [1 ]
Yan, GJ [1 ]
机构：
[1] Beijing Normal Univ, Dept Math, Beijing 100875, Peoples R China
来源：
IGARSS 2002: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM AND 24TH CANADIAN SYMPOSIUM ON REMOTE SENSING, VOLS I-VI, PROCEEDINGS: REMOTE SENSING: INTEGRATING OUR VIEW OF THE PLANET | 2002年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we take the kernel-driven model as an example, focus on the information contents definition and calculation of multi-angular remote sensing (MARS) data. We study four methods to measure the information content of MARS data: Fisher statistic, information entropy, determinant and sum of the diagonal elements of the information matrix, how to use the Fisher statistic theory and information entropy to measure the information contents of MARS data, to calculate the information contents of the dataset on the three unknowns for different subset of the data. The analyses show that information entropy is a good tool for measuring information content of MARS data.
引用
收藏
页码：1636 / 1638
页数：3
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