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

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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Bibliographic Details
Main Authors: Yi Zhang, Zebin Wu, Jin Sun, Yan Zhang, Yaoqin Zhu, Jun Liu, Qitao Zang, Antonio Plaza
Format: Article
Language:English
Published: MDPI AG 2018-10-01
Series:Sensors
Subjects:
hyperspectral images
anomaly detection
distributed and parallel computing
apache spark
clouds
Online Access:https://www.mdpi.com/1424-8220/18/11/3627

Internet

https://www.mdpi.com/1424-8220/18/11/3627

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