SPECTRAL UNMIXING USING LINEAR UNMIXING UNDER SPATIAL AUTOCORRELATION CONSTRAINTS

被引:6
|
作者
Song, Xianfeng [1 ,2 ]
Jiang, Xiaoguang [2 ]
Rui, Xiaoping [1 ]
机构
[1] Chinese Acad Sci, Grad Univ, Beijing 100049, Peoples R China
[2] Chinese Acad Sci, Acad Opto Elect, Beijing 100190, Peoples R China
基金
中国国家自然科学基金;
关键词
Linear spectral unmixing; spatial autocorrelation; genetic algorithm; HYPERSPECTRAL DATA;
D O I
10.1109/IGARSS.2010.5649735
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
This paper presents a spectral unmixing approach that is implemented using linear unminxing method by a genetic algorithm. The unmixing is constrained not only by the negativity and sum-to-one of the abundances of endmembers at each pixel but also by the spatial autocorrelation of their abundances among eight neighbor pixels. The Moran's I indices are proposed to describe the spatial autocorrelation among a pixel and its neighborhood. Based on the above constraints, the objective of unmixing by genetic algorithm is to minimize the mean square error of mixed spectral values. We tested this approach using Chinese HJ-satellite images and obtained an acceptable result.
引用
收藏
页码:975 / 978
页数:4
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