Particle Swarm Optimization Algorithm for Unmixing Hyperspectral Image

被引：0
|
作者：
Maneiro, Mariana [1 ]
Xu XiaoJian [1 ]
机构：
[1] Beihang Univ, Sch Elect & Informat Engn, Beijing 100191, Peoples R China
来源：
2010 IEEE 10TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS (ICSP2010), VOLS I-III | 2010年
关键词：
Endmembers Extraction; Hyperspectral Unmixing; Particle Swarm Optimization; Minimum volume simplex;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
An end-member extraction method for spectral unmixing that is based on Particle Swarm Optimization (PSO) is developed and presented in this paper. The objective function minimized by PSO is the volume of the simplex containing the hyperspectral vectors, following the geometrical characteristics inherent to the data sets. The proposed algorithm has been successfully applied to synthetic hyperspectral image sets, showing to be very fast and be able to determine a high number of endmembers. The experimental results of the proposed algorithm are encouraging. The performance of different versions of PSO is also investigated.
引用
收藏
页码：897 / 901
页数：5
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