Anomaly Detection for Hyperspectral Images Based on Improved Low-Rank and Sparse Representation and Joint Gaussian Mixture Distribution

Anomaly Detection for Hyperspectral Images Based on Improved Low-Rank and Sparse Representation and Joint Gaussian Mixture Distribution

The background dictionary used in the hyperspectral images anomaly detection based on low-rank and sparse representation (LRASR) contains both target information and background information which will result in low detection accuracy. In response to this problem, this article proposes an improved hyp...

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Bibliographic Details
Main Authors: Qiong Ran, Zedong Liu, Xiaotong Sun, Xu Sun, Bing Zhang, Qiandong Guo, Jinnian Wang
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Anomaly detection
dictionary construction
hyperspectral image (HSI)
low-rank and sparse representation (LRASR)
mixture of Gaussian (MOG)
Online Access:https://ieeexplore.ieee.org/document/9448438/

Internet

https://ieeexplore.ieee.org/document/9448438/

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