| 一种双正则项全变差高光谱图像去噪算法 |
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| 作者姓名： | Li T Chen XM Chen G Xue B Ni GQ |
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| 作者单位： | 1. 北京理工大学光电学院,北京,100081;北京理工大学光电成像技术与系统教育部重点实验室,北京,100081
2. 北京理工大学光电学院,北京,100081;Polytechnic Institute of New York University,Brooklyn,NY,USA 11201 |
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| 基金项目： | 国家(863计划)项目(2008AA121103)资助 |
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| 摘 要： | 受传感器特性影响,高光谱图像中的噪声在各个维度都有体现。噪声的存在降低了高光谱图像中信息的有效性,在进行地物分类前必须采用适当的算法对噪声予以去除。文章针对高光谱图像的噪声特性,提出了一种基于全变差的高光谱图像去噪算法。该算法将经典二维图像全变差去噪模型推广至三维形式,提出了采用双正则项及相应的调整参数的目标函数,在三维空间中完成新目标函数的离散化,并采用基于优化-最小化算法的迭代方法对目标函数进行优化与求解。对星载Hyperion成像光谱仪数据的实验表明,适当的设置调整参数,该方法可很好地提高高光谱图像的各波段信噪比、平滑光谱曲线并保留细节特征,其去噪效果优于经典的MNF去噪算法及Savitzky-Golay滤波方法。
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| 关 键 词： | 全变差 高光谱图像 去噪 |
A noise reduction algorithm of hyperspectral imagery using double-regularizing terms total variation |
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| Li T,Chen XM,Chen G,Xue B,Ni GQ.A noise reduction algorithm of hyperspectral imagery using double-regularizing terms total variation[J].Spectroscopy and Spectral Analysis,2011,31(1):16-20. |
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| Authors: | Li Ting Chen Xiao-Mei Chen Gang Xue Bo Ni Guo-Qiang |
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| Institution: | LI Ting1,2,CHEN Xiao-mei1,2*,CHEN Gang1,3,XUE Bo1,NI Guo-qiang1,2 1.School of Optoelectronics,Beijing Institute of Technology,Beijing 100081,China 2.Key Laboratory of Photoelectronic Imaging Technology and System(Beijing Institute of Technology),Ministry of Education of China,China 3.Polytechnic Institute of New York University,Brooklyn,NY,USA 11201 |
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| Abstract: | In the present paper,an effective total variation denoising algorithm is proposed based on hyperspectral imagery noise characteristics.The new algorithm generalizes the classical total variation denoising algorithm for two-dimensional images to a three-dimensional formulation.Considering the fact that the noise of hyperspectral imagery shows different characteristics in spatial domain and spectral domain respectively,the objective function of the proposed total variation algorithm is improved by utilizing d... |
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| Keywords: | Hyperspectral imagery Total variation Denoising |
| 本文献已被 CNKI 万方数据 PubMed 等数据库收录！ |
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