Hyperspectral Anomaly Detection via Merging Total Variation Into Low-Rank Representation
Anomaly detection (AD) aiming to locate targets distinct from the surrounding background spectra remains a challenging task in hyperspectral applications. The methods based on low-rank decomposition utilize the inherent low-rank characteristic of hyperspectral images (HSIs), which has attracted grea...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10643646/ |
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