| 基于模糊核主成分分析的高光谱遥感影像特征提取研究 |
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| 引用本文： | 沈照庆,陶建斌.基于模糊核主成分分析的高光谱遥感影像特征提取研究[J].国土资源遥感,2009(3):41-44,99. |
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| 作者姓名： | 沈照庆 陶建斌 |
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| 作者单位： | 武汉大学遥感信息工程学院,武汉,430079 |
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| 基金项目： | 国家重点基础研究发展计划(973)项目"对地观测数据-空间信息-地学知识的转化机理" |
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| 摘 要： | 主成分分析(PCA)是一种基于数理统计的线性特征变换方法,对线性结构数据的分析非常有效,但是对非线性的高光谱遥感影像数据,容易造成信息丢失和失真.本文引人模式识别中的模糊理论和核理论,有效克服了以上缺点,得到了很好的影像特征提取效果.
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| 关 键 词： | 模糊集 核PCA 高光谱遥感影像 特征提取 |
HYPERSPECTRAL REMOTE SENSING IMAGE FEATURE EXTRACTION BASED ON FUZZY KERNEL PRINCIPAL COMPONENT ANALYSIS |
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| SHEN Zhao-qing,TAO Jian-bin.HYPERSPECTRAL REMOTE SENSING IMAGE FEATURE EXTRACTION BASED ON FUZZY KERNEL PRINCIPAL COMPONENT ANALYSIS[J].Remote Sensing for Land & Resources,2009(3):41-44,99. |
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| Authors: | SHEN Zhao-qing TAO Jian-bin |
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| Institution: | School of Remote Sensing and Information Engineering;Wuhan University;Wuhan 430079;China |
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| Abstract: | The principal component analysis(PCA),a classical linear feature transformation method based on mathematical statistics,is effective in the analysis of linear data.Nevertheless,PCA is likely to result in distortion and loss of data information for non-linear hyperspectral Remote Sensing(RS)image data.In this paper,the fuzzy mathematical theory and the theory of kernel in pattern recognition is proposed for the purpose of effectively overcoming the shortcomings of traditional PCA.The test results show that t... |
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| Keywords: | Fuzzy sets Kernel PCA Hyperspectral RS images Feature extraction |
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