基于最大似然分类法的面积估计改进模型

基于最大似然分类法的面积估计改进模型

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Initial contribute: 2018-12-04

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Affiliation:  
岳天祥编著
Email:  
yue@lreis.ac.cn
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Method-focused categoriesData-perspectiveGeostatistical analysis

Model Description

Chinese {{currentDetailLanguage}} Chinese

基于最大似然分类法的面积估计改进模型

(1)    最大似然度法的判别函数:

式中,F是判别函数;X是数据谱段中考察像素相应的数据矢量;M是类型i在所有数据谱段上的平均矢量;C是类型i的方差-协方差矩阵。

(2)    误差概率估计与修正分类方法:

式中,是类型i相对于类型j的委托误差概率;是类型i相对于类型j的忽略误差概率;是误差矩阵的矩阵元。

(3)    对给定的某个像素,如果P是某类型中某个元素的修正判别的优先概率,可以根据最大似然度等效于判别函数最小化而把这个像素归于这个类型:

     根据这个理论,修正的最大似然度分类法即是使下面函数最小化:

式中,i是初始分配的类型组;j是目前考察的类型组。

参考文献

    Maselli F,Conese C,Zipoli G et al:利用误差概率改进基于最大似然分类法的面积估计。Remote Sensing of Environment,1990,31

 

How to Cite

《资源环境数学模型手册》 (2018). 基于最大似然分类法的面积估计改进模型, Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/eb5879f0-3345-468f-9d3d-d164d1475e0c
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Last modifier : 
haolingchen
Last modify time : 
2020-10-29
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Contributor

Initial contribute: 2018-12-04

Co-contributor(s)

Authorship

Affiliation:  
岳天祥编著
Email:  
yue@lreis.ac.cn
Homepage:  
View
Is authorship not correct? Feedback

History

Last modifier : 
haolingchen
Last modify time : 
2020-10-29
Modify times : 
View History

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