| 面向高光谱矿物填图的多特征结合降维方法研究 |
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| 引用本文： | 苏余斌,詹云军,黄解军,叶发旺,张川.面向高光谱矿物填图的多特征结合降维方法研究[J].地质科技通报,2015,34(5):206-211. |
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| 作者姓名： | 苏余斌 詹云军 黄解军 叶发旺 张川 |
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| 作者单位： | 1. 武汉理工大学资源与环境工程学院, 武汉 430070; |
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| 基金项目： | 中央高校基本科研业务费专项资金资助项目(2014-IV-141) |
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| 摘 要： | 高光谱影像具有图谱合一的特点,图像空间信息是遥感影像的重要信息,但以往基于最佳波段选择的降维方法中只考虑基于灰度统计的特征空间信息,忽视了图像空间信息,而且计算量大。综合高光谱遥感影像的特征空间与图像空间信息,提出了一种多特征结合的高光谱影像降维方法并应用于矿物填图中。统计分析波段相关性并划分不同特征子空间;计算各波段的分形维数,在各子空间选择分形维数较小的波段作为候选波段;在候选波段中,计算待识别地物光谱间的相关系数,并快速选择出最佳波段组合。经实验,应用该方法选出的最佳波段组合影像清晰、不同蚀变矿物对比明显,根据特征选择提取出的矿物蚀变信息与应用成熟的光谱角制图(SAM)提取结果大致相同,表明结合图像空间和特征空间的降维方法能够选择出理想的波段组合,有效降低高光谱数据的维数,信息提取效果好。
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| 关 键 词： | 高光谱遥感 波段选择 图像空间 特征空间 矿物填图 |
| 收稿时间： | 2014-10-21 |
Dimension Reduction Method Combining Multi-Features for Hyperspectral Mineral Mapping |
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| Affiliation: | 1. School of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan 430070, China;2. National Key Laboratory of Remote Sensing Information and Image Analysis Technique, Beijing Research Institute of Uranium Geology, Beijing 100029, China |
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| Abstract: | Hyperspectral remote sensing image is important in image spatial information and spectral information.However,the traditional dimension reduction method based on optimal band selection only considers the feature space information based on gray statistical characteristics,but ignores the image spatial information,thus causing a large amount of calculation.This paper,combined with the feature space information and image space information of hyperspectral remote sensing,proposes a new dimension reduction method combining multi-features of hyperspectral images and applies the method in mineral mapping.In this method,band correlation is first analyzed statistically and divided into different feature subspace.Then,fractal dimension of each band is computed and the band with the smallest fractal dimension is chosen as a candidate band in each subspace.Finally,calculation is made of the correlation coefficient between the spectrum of ground objects to be identified in the candidate bands so as to select quickly the optimal band combination.The result shows that,the image of the optimal band combination selected with this method is clear and shows an obvious correlation between different altered minerals.Besides,the mineral alteration information extracted by the method of mature spectral angle mapping(SAM)is roughly the same as the information extracted according to the feature selection.The above results indicates that the dimension reduction method combined with the image space and feature space can help to choose the ideal band combination.This reduces the dimension of hyperspectral image data and has a good effect of information extraction. |
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