[1]宋义刚,吴泽彬,韦志辉,等.稀疏性高光谱解混方法研究[J].南京理工大学学报(自然科学版),2013,37(04):486.
 Song Yigang,Wu Zebin,Wei Zhihui,et al.Survey of sparsity constrained hyperspectral unmixing[J].Journal of Nanjing University of Science and Technology,2013,37(04):486.
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稀疏性高光谱解混方法研究
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
37卷
期数:
2013年04期
页码:
486
栏目:
出版日期:
2013-08-31

文章信息/Info

Title:
Survey of sparsity constrained hyperspectral unmixing
作者:
宋义刚1吴泽彬12韦志辉1孙 乐1刘建军1
南京理工大学 1.计算机科学与工程学院,江苏 南京 210094; 2.连云港研究院,江苏 连云港 222006
Author(s):
Song Yigang1Wu Zebin12Wei Zhihui1Sun Le1Liu Jianjun1
1.School of Computer Science and Engineering; 2.Lianyungang Institute,NUST,Lianyungang 222006,China
关键词:
高光谱 稀疏性 解混
Keywords:
hyperspectral sparsity unmixing
分类号:
TP391
文献标志码:
A
摘要:
该文在分析基于几何先验和统计先验的传统线性高光谱解混方法的基础上,研究了基于稀疏性先验的高光谱解混模型和算法,对基于光谱库的稀疏性高光谱解混方法和基于非负矩阵分解的稀疏性高光谱解混方法进行了分析比较和性能测试,验证了稀疏性高光谱解混方法的有效性,讨论了相关研究要点和后续研究思路。
Abstract:
On the basis of analyzing traditional linear hyperspectral unmixing methods based on the geometrical prior and the statistical prior,sparsity constrained hyperspectral unmixing models and algorithms are studied.The methods of sparsity constrained hyperspectral unmixing based on spectral library and those based on non-negative matrix factorization are reviewed and compared with each other.The effectiveness of the sparse hyperspectral unmixing is demonstrated.The corresponding perspectives on the future are presented.

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相似文献/References:

[1]吴泽彬,韦志辉,孙乐,等.基于迭代加权L1 正则化的高光谱混合像元分解[J].南京理工大学学报(自然科学版),2011,(04):431.
 WU Ze-bin,WEI Zhi-hui,SUN Le,et al.Hyperspectral Unmixing Based on Iterative Weighted L1 Regularization[J].Journal of Nanjing University of Science and Technology,2011,(04):431.

备注/Memo

备注/Memo:
收稿日期:2012-12-24 修回日期:2013-06-20
基金项目:国家自然科学基金(61101194); 江苏省自然科学基金(BK2011701); 江苏省“六大人才高峰”项目(WLW-011); 高等学校博士学科点专项科研基金资助项目(20113219120024); 中国地质调查局工作项目(1212011120227); 航遥中心对地观测技术工程实验室开放课题资助
作者简介:宋义刚(1967-),男,博士生,主要研究方向:遥感信息处理,E-mail:songyigang@sina.com; 通讯作者:吴泽彬(1981-),男,副教授,主要研究方向:遥感信息处理、计算机仿真,E-mail:wuzb@njust.edu.cn。
更新日期/Last Update: 2013-08-31