Sparse and low-rank matrix decomposition-based method for hyperspectral anomaly detection
Author:
Affiliation:
1. Ankara Yildirim Beyazit University, Faculty of Engineering and Natural Science, Computer Engineering
2. Istanbul Technical University, Informatics Institute, Maslak, Istanbul
Publisher
SPIE-Intl Soc Optical Eng
Subject
General Earth and Planetary Sciences
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4. Ensemble-Based Information Retrieval With Mass Estimation for Hyperspectral Target Detection;IEEE Transactions on Geoscience and Remote Sensing;2022
5. A Hyperspectral Anomaly Detection Method Based on Low-Rank and Sparse Decomposition With Density Peak Guided Collaborative Representation;IEEE Transactions on Geoscience and Remote Sensing;2022
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