A Distributed Parallel Algorithm Based on Low-Rank and Sparse Representation for Anomaly Detection in Hyperspectral Images

Anomaly detection aims to separate anomalous pixels from the background, and has become an important application of remotely sensed hyperspectral image processing. Anomaly detection methods based on low-rank and sparse representation (LRASR) can accurately detect anomalous pixels. However, with the...

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Veröffentlicht in:	Sensors (Basel, Switzerland) Jg. 18; H. 11; S. 3627
Hauptverfasser:	Zhang, Yi, Wu, Zebin, Sun, Jin, Zhang, Yan, Zhu, Yaoqin, Liu, Jun, Zang, Qitao, Plaza, Antonio
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI 25.10.2018 MDPI AG
Schlagworte:	anomaly detection apache spark clouds distributed and parallel computing hyperspectral images anomaly detection clouds distributed and parallel computing hyperspectral images apache spark
ISSN:	1424-8220, 1424-8220
Online-Zugang:	Volltext
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