半导体光电, 2020, 41 (1): 141, 网络出版: 2020-04-13  

联合空间信息的改进低秩稀疏矩阵分解的高光谱异常目标检测

Joint Spatial Information and Improved Low-rank and Sparse Matrix Decomposition-based Anomaly Target Detection for Hyperspectral Imagery
作者单位
1 陆军工程大学石家庄校区 电子与光学工程系, 石家庄 050003
2 解放军31681部队, 甘肃 天水 741000
3 解放军68129部队, 兰州 730000
引用该论文

张炎, 华文深, 黄富瑜, 严阳, 王强辉, 索文凯. 联合空间信息的改进低秩稀疏矩阵分解的高光谱异常目标检测[J]. 半导体光电, 2020, 41(1): 141.

ZHANG Yan, HUA Wenshen, HUANG Fuyv, YAN Yang, WANG Qianghui, SUO Wenkai. Joint Spatial Information and Improved Low-rank and Sparse Matrix Decomposition-based Anomaly Target Detection for Hyperspectral Imagery[J]. Semiconductor Optoelectronics, 2020, 41(1): 141.

参考文献

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张炎, 华文深, 黄富瑜, 严阳, 王强辉, 索文凯. 联合空间信息的改进低秩稀疏矩阵分解的高光谱异常目标检测[J]. 半导体光电, 2020, 41(1): 141. ZHANG Yan, HUA Wenshen, HUANG Fuyv, YAN Yang, WANG Qianghui, SUO Wenkai. Joint Spatial Information and Improved Low-rank and Sparse Matrix Decomposition-based Anomaly Target Detection for Hyperspectral Imagery[J]. Semiconductor Optoelectronics, 2020, 41(1): 141.

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