An Efficient and Robust Framework for Hyperspectral Anomaly Detection

An Efficient and Robust Framework for Hyperspectral Anomaly Detection

Hyperspectral images contain distinguishing spectral information and show great potential in the anomaly detection (AD) task which aims to extract discrepant targets from the background. However, most of the popular hyperspectral AD techniques are time consuming and suffer from poor detection perfor...

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Bibliographic Details
Main Authors: Linbo Tang, Zhen Li, Wenzheng Wang, Baojun Zhao, Yu Pan, Yibing Tian
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Remote Sensing
Subjects:
hyperspectral image
anomaly detection
principal component analysis
robustness
Online Access:https://www.mdpi.com/2072-4292/13/21/4247

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https://www.mdpi.com/2072-4292/13/21/4247

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