Spectral unmixing and image classification supported by spatial knowledge

被引：1
|
作者：
Zhang, B [1 ]
Zhang, X [1 ]
Liu, LY [1 ]
Zheng, L [1 ]
Tong, QX [1 ]
机构：
[1] Chinese Acad Sci, Lab Remote Sensing Informat Sci, Inst Remote Sensing Applicat, Beijing 100101, Peoples R China
来源：
MULTISPECTRAL AND HYPERSPECTRAL REMOTE SENSING INSTRUMENTS AND APPLICATIONS | 2003年 / 4897卷
关键词：
hyperspectral data; spectral unmixing; thematic map;
D O I：
10.1117/12.467408
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
Usually the spectral unmixing and endmember extraction were based on the spectral statistics algorithm. In this paper, spatial knowledge, such as field patch information, was involved in the pure pixel selecting. In this way, endmember extraction was not only carried out in spectral space but also considering the spatial location of pixels. In addition, these known background information can also improve the accuracy of image classification, and also can be used to. intellectually separate pixels and evaluate each sub-pixels different attributes.
引用
收藏
页码：279 / 283
页数：5
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