| 张量组稀疏表示的高光谱图像去噪算法 |
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| 引用本文： | 王忠美,杨晓梅,顾行发.张量组稀疏表示的高光谱图像去噪算法[J].测绘学报,2017,46(5):614-622. |
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| 作者姓名： | 王忠美 杨晓梅 顾行发 |
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| 作者单位： | 1. 电子科技大学 四川 成都 610054;2. 中国科学院地理科学与资源研究所, 北京 100101;3. 中国科学院遥感与数字地球研究所, 北京 100101 |
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| 基金项目： | 国家重点研发计划，国家自然科学基金(41671436)
The NationalKey Research and Development Program of China，The National Science Foundation of China under Grant |
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| 摘 要： | 提出了一种基于张量组稀疏表示的高光谱遥感影像降噪。高光谱影像数据可视为三阶张量。首先,高光谱图像被划分为小的张量分块,然后,对相似的张量分块进行聚类,并对聚类分组进行稀疏表示。基于高光谱图像的空间非局部自相似性和光谱相关性,将张量组稀疏表示模型分解为一系列无约束低秩张量的近似问题,进而通过张量分解进行求解。对模拟和真实高光谱数据进行试验,验证了该算法的有效性。
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| 关 键 词： | 高光谱图像 张量 稀疏表示 非局部相似性 |
| 收稿时间： | 2015-08-21 |
| 修稿时间： | 2017-03-05 |
Hyperspectral Image Denoising Based on Tensor Group Sparse Representation |
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| WANG Zhongmei,YANG Xiaomei,GU Xingfa.Hyperspectral Image Denoising Based on Tensor Group Sparse Representation[J].Acta Geodaetica et Cartographica Sinica,2017,46(5):614-622. |
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| Authors: | WANG Zhongmei YANG Xiaomei GU Xingfa |
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| Institution: | 1. University of Electronic Science and Technology of China, Chengdu 610054, China;2. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;3. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China |
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| Abstract: | A novel algorithm for hyperspectral image (HSI)denoising is proposed based on tensor group sparse representation.A HSI is considering as 3 order tensor.First,a HSI is divided into small tensor blocks.Second,similar blocks are gathered into clusters,and then a tensor group sparse representation model is constructed based on every cluster.Through exploiting HSI spectral correlation and nonlocal similarity over space,the model constrained tensor group sparse representation can be decomposed into a series of unconstrained low-rank tensor approximation problems,which can be solved using the tensor decomposition technique.The experiment results on the synthetic and realhyperspectral remote sensing images demonstrate the effectiveness of the proposed approach. |
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| Keywords: | hyperspectral image tensor sparse representation nonlocal similarity |
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