Weighted Sparseness-Based Anomaly Detection for Hyperspectral Imagery

Anomaly detection of hyperspectral remote sensing data has recently become more attractive in hyperspectral image processing. The low-rank and sparse matrix decomposition-based anomaly detection algorithm (LRaSMD) exhibits poor detection performance in complex scenes with multiple background edges a...

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Detalles Bibliográficos
Autores principales: Lian, Xing, Zhao, Erwei, Zheng, Wei, Peng, Xiaodong, Li, Ang, Zhen, Zheng, Wen, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9959882/
https://www.ncbi.nlm.nih.gov/pubmed/36850660
http://dx.doi.org/10.3390/s23042055

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9959882/
https://www.ncbi.nlm.nih.gov/pubmed/36850660
http://dx.doi.org/10.3390/s23042055

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