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| 基于粒子群算法的高光谱影像端元提取技术 | |
| 引用本文： | 陈伟,余旭初,王鹤,闻兵工,靳克强.基于粒子群算法的高光谱影像端元提取技术[J].测绘科学,2011,36(4):16-18,30. |
| 作者姓名： | 陈伟 余旭初 王鹤 闻兵工 靳克强 |
| 作者单位： | 1. 信息工程大学测绘学院,郑州,450052 2. 北京望神州科技有限公司,北京,100020 3. 78155部队,成都,610036 4. 96633部队,北京,100096 |
| 摘 要： | 基于凸面几何学理论,由端元作为角点的单形体的体积应该是最大的.著名的N-FINDR和SGA算法正是基于以上理论,通过在数据云中寻找体积最大的单形体来实现端元的自动提取.本文利用粒子群优化(PS0)技术,基于凸面几何学理论,设计了一个新的端元提取算法.利用模拟和真实高光谱影像对其进行了实验,并将其结果与N-FINDR和S... |
| 关 键 词： | 高光谱影像 粒子群算法 线性混合模型 端元提取 N-FINDR |
Particle swarm optimization for endmember extraction in hyperspectral imagery |
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| CHEN Wei,YU Xu-chu,WANG He,WEN Bing-gong,JIN Ke-qiang.Particle swarm optimization for endmember extraction in hyperspectral imagery[J].Science of Surveying and Mapping,2011,36(4):16-18,30. | |
| Authors: | CHEN Wei YU Xu-chu WANG He WEN Bing-gong JIN Ke-qiang |
| Institution: | ④(①Institute of Surveying and Mapping,Information Engineering University,Zhengzhou 450052,China;②Digital LandView Technology Company Limited,Beijing 100020,China;③Troops 78155,Chengdu 610036,China;④Troops 96633,Beijing 100096,China) |
| Abstract: | Based on convex geometry theory,the simplex with vertices that are given by the spectra of the endmembers has the biggest volume.N-FINDR and SGA which based on convex geometry theory are popular endmember extraction algorithms.They select the simplex which has the biggest volume in the data cloud to extracting endmembers automatically.An endmember extraction method that is based on Particle Swarm Optimization(PSO) and convex geometry theory was developed in this paper.It carried out the experiments by simulative and real hyperspectral imageries.As well as it compared and analyzed the results among the PSO,N-FINDR and SGA. |
| Keywords: | hyperspectral imagery particle swarm optimization linear mixture model endmember extraction N-FINDR |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |