A Low-Rank and Sparse Matrix Decomposition- Based Dictionary Reconstruction and Anomaly Extraction Framework for Hyperspectral Anomaly Detection

Yichu Xu
Yichu Xu
Shizhen Chang
Shizhen Chang

IEEE Geoscience and Remote Sensing Letters, pp. 1248-1252, 2020.

Cited by: 0|Bibtex|Views18|DOI:https://doi.org/10.1109/LGRS.2019.2943861
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Other Links: dblp.uni-trier.de

Abstract:

As one of the important applications of hyperspectral imagery (HSI) processing, the Mahalanobis distance-based detector in anomaly detection used to extract knowledge from the background and then calculate the Mahalanobis distance to obtain the detection result. Different from the previous work, a novel low-rank and sparse matrix decompos...More

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