| 基于加权仿射变换算法的高光谱数据降维 |
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| 引用本文： | 高燕,杨小远. 基于加权仿射变换算法的高光谱数据降维[J]. 河南科学, 2014, 0(8): 1451-1456 |
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| 作者姓名： | 高燕 杨小远 |
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| 作者单位： | 北京航空航天大学 数学与系统科学学院 教育部信息与行为实验室,北京,100191 |
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| 摘 要： | 提出一种基于噪声白化和端元提取的加权仿射变换算法用于高光谱图像数据降维,相比较于基于端元提取的仿射变换算法,通过该算法降维后数据的信噪比更高,同时对原始信息的保存量更大,波段之间的相关性更低,从而表明了该算法的有效性.
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| 关 键 词： | 高光谱图像数据 噪声白化 数据降维 仿射变换 端元提取 |
Hyperspectral Data Dimension Reduction Based on Weighted Robust Affine Set Fitting Algorithm |
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| Gao Yan,Yang Xiaoyuan. Hyperspectral Data Dimension Reduction Based on Weighted Robust Affine Set Fitting Algorithm[J]. Henan Science, 2014, 0(8): 1451-1456 |
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| Authors: | Gao Yan Yang Xiaoyuan |
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| Affiliation: | (Information and Behavior Laboratory of the Education Ministry of China, Institute of Mathematics and System Science, Beihang University, Beijing 100191, China) |
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| Abstract: | A robust affine set fitting algorithm based on noise whitening and endmember extraction for hyperspectral image data dimension reduction is presented in this paper. Compared to the effect of robust affine set fitting algorithm based on endmember extraction, the data received by this method has a higher signal-to-noise ratio, and the original information is retained larger, at the same time the correlation of adjacent bands is lower, so as to verify the effectiveness of the proposed algorithm. |
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| Keywords: | hyperspectral image data noise whitening dimension reduction robust affine set fitting algorithm endmember extraction |
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