| 端元约束下的高光谱混合像元非负矩阵分解 |
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| 引用本文： | 吴波,赵银娣,周小成. 端元约束下的高光谱混合像元非负矩阵分解[J]. 计算机工程, 2008, 34(22): 229-230 |
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| 作者姓名： | 吴波 赵银娣 周小成 |
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| 作者单位： | 1. 福州大学福建省空间信息工程研究中心,福州,350002
2. 中国矿业大学环境与测绘学院,徐州,221116 |
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| 基金项目： | 国家自然科学基金资助项目(40801181); 福建省自然科学基金资助项目(D0710012) |
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| 摘 要： | 提出一种端元约束条件下的非负矩阵分解方法来自动反演混合像元组分。以端元光谱之间的差距为约束条件，使得目标函数综合了影像的分解误差和端元光谱的影响，并以最大后验概率方法导出了限制性非负矩阵分解的迭代算法。成像光谱数据实验结果表明该方法能够自动提取影像的端元光谱矩阵与组分信息，且分解精度比IEA方法高。
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| 关 键 词： | 非负矩阵分解 混合像元 约束 高光谱 |
| 修稿时间： | |
Unmixing Mixture Pixels of Hyperspectral Imagery Using Endmember Constrained Nonnegative Matrix Factorization |
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| WU Bo,ZHAO Yin-di,ZHOU Xiao-cheng. Unmixing Mixture Pixels of Hyperspectral Imagery Using Endmember Constrained Nonnegative Matrix Factorization[J]. Computer Engineering, 2008, 34(22): 229-230 |
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| Authors: | WU Bo ZHAO Yin-di ZHOU Xiao-cheng |
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| Affiliation: | (1. Spatial Information Research Center of Fujian Province, Fuzhou University, Fuzhou 350002; 2. School of Environment Science and Spatial Informatics, China Unviersity of Mining and Technology, Xuzhou 221116) |
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| Abstract: | An endmember constrained Nonnegative Matrix Factorization(NMF) method for mixture pixels unmixing is proposed. A penalty function imposed by maximizing difference between endmembers among all possible simplexes is presented in the image. The maximum posterior probabilistic method is utilized to formulate a novel iterative algorithm by trading off abundance nonnegative attribution and endmember difference. Experimental result with PHI data shows the proposed algorithm is an alternative approach for endmember abstraction and abundance estimation. Comparison with IEA validates the efficience of the proposed method. |
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| Keywords: | Nonnegative Matrix Factorization(NMF) mixture pixels constrainted hyperspectral imagery |
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