| 基于约束非负矩阵分解的高光谱图像解混 |
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| 引用本文： | 方帅,王金明,曹风云.基于约束非负矩阵分解的高光谱图像解混[J].激光与光电子学进展,2019,56(16):14-23. |
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| 作者姓名： | 方帅 王金明 曹风云 |
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| 作者单位： | 合肥工业大学计算机与信息学院人工智能与数据挖掘研究室,安徽合肥,230601;合肥工业大学工业安全与应急技术安徽省重点实验室,安徽合肥230601;合肥师范学院计算机学院,安徽合肥230601 |
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| 基金项目： | 国家自然科学基金;国家自然科学基金;中央高校基本科研业务费专项;中央高校基本科研业务费专项 |
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| 摘 要： | 光谱解混可以有效提升高光谱图像的利用效率。非负矩阵分解(NMF)常用于寻找非负数据的线性表示,可以有效解决混合像元问题。基于丰度的稀疏性和图像局部不变性提出一种高光谱解混算法。对丰度采取稀疏性约束和基于拉普拉斯矩阵的图正则项约束,构造了一个新的目标函数,端元和丰度在经过若干次迭代后取得了较好的解混合结果。该算法在模拟和真实数据上都进行了有效性验证,实验结果证明所提算法具有良好的解混性能。
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| 关 键 词： | 图像处理 光谱解混合 非负矩阵分解 端元 丰度 |
Hyperspectral Image Unmixing Based on Constrained Nonnegative Matrix Factorization |
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| Fang Shuai,Wang Jinming,Cao Fengyun.Hyperspectral Image Unmixing Based on Constrained Nonnegative Matrix Factorization[J].Laser & Optoelectronics Progress,2019,56(16):14-23. |
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| Authors: | Fang Shuai Wang Jinming Cao Fengyun |
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| Affiliation: | (Department of Artificial Intelligence and Data Mining, School o f Computer Science and Inform ation Engineering, Hefei University of Techiology, Hefei, Anhui 230601, China;Anhui Provincial Key Laboratory of Industry Safety and Emergency Technology,Hefei University of Technologyt Hefei,Anhui 230601,China;School of Computer Science and Techriology, Hefei Normal University, Hefei, Anhui 230601, China) |
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| Abstract: | Fang Shuai;Wang Jinming;Cao Fengyun(Department of Artificial Intelligence and Data Mining, School o f Computer Science and Inform ation Engineering, Hefei University of Techiology, Hefei, Anhui 230601, China;Anhui Provincial Key Laboratory of Industry Safety and Emergency Technology,Hefei University of Technologyt Hefei,Anhui 230601,China;School of Computer Science and Techriology, Hefei Normal University, Hefei, Anhui 230601, China) |
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| Keywords: | image processing spectral unmixing nonnegative m atrix factorization endm em ber abundance |
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