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基于光谱信息散度的光谱解混算法

徐 州 赵慧洁

徐 州, 赵慧洁. 基于光谱信息散度的光谱解混算法[J]. 北京航空航天大学学报, 2009, 35(9): 1091-1094.
引用本文: 徐 州, 赵慧洁. 基于光谱信息散度的光谱解混算法[J]. 北京航空航天大学学报, 2009, 35(9): 1091-1094.
Xu Zhou, Zhao Huijie. Advanced spectral unmixing algorithm based on spectral information divergence[J]. Journal of Beijing University of Aeronautics and Astronautics, 2009, 35(9): 1091-1094. (in Chinese)
Citation: Xu Zhou, Zhao Huijie. Advanced spectral unmixing algorithm based on spectral information divergence[J]. Journal of Beijing University of Aeronautics and Astronautics, 2009, 35(9): 1091-1094. (in Chinese)

基于光谱信息散度的光谱解混算法

基金项目: 中国地质调查局资助项目(1212010816033);国家863计划资助项目(2008AA121102);长江学者和创新团队发展计划资助项目(IRT0705)
详细信息
    作者简介:

    徐 州(1984-),浙江台州人,硕士生,yurenzhou 2000@163.com.

  • 中图分类号: TP 751.1

Advanced spectral unmixing algorithm based on spectral information divergence

  • 摘要: 光谱解混是高光谱遥感定量化的关键,提出了一种基于光谱信息散度和光谱混合分析的光谱解混改进算法(SID-SMA,Spectral Information Divergence-Spectral Mixed Analysis).以光谱信息散度判定最优端元子集,端元选择时采用端元的初选和二次选择来提高端元选择的精度,得到较小的丰度估计误差.通过光谱库模拟数据的结果可以看出,SID-SMA的端元选择精度和丰度估计精度要优于其他算法,当信噪比为100∶ 1时,算法端元选择正确率达到了99.8%,29个端元的丰度估计总误差小于0.1,并且算法的速度较快.

     

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出版历程
  • 收稿日期:  2008-07-21
  • 网络出版日期:  2009-09-30

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