Systematic Review of Anomaly Detection in Hyperspectral Remote Sensing Applications
Hyperspectral sensors are passive instruments that record reflected electromagnetic radiation in tens or hundreds of narrow and consecutive spectral bands. In the last two decades, the availability of hyperspectral data has sharply increased, propelling the development of a plethora of hyperspectral...
Main Authors: | Ivan Racetin, Andrija Krtalić |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-05-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/11/11/4878 |
Similar Items
-
An Overview of Background Modeling for Detection of Targets and Anomalies in Hyperspectral Remotely Sensed Imagery
by: Stefania Matteoli, et al.
Published: (2014-01-01) -
Adjusted Spectral Matched Filter for Target Detection in Hyperspectral Imagery
by: Lianru Gao, et al.
Published: (2015-05-01) -
Sparse Representation Based Hyperspectral Anomaly Detection via Adaptive Background Sub-Dictionaries
by: Yi Lu, et al.
Published: (2021-01-01) -
Structured Background Modeling for Hyperspectral Anomaly Detection
by: Fei Li, et al.
Published: (2018-09-01) -
Hyperspectral Anomaly Detection Through Sparse Representation With Tensor Decomposition-Based Dictionary Construction and Adaptive Weighting
by: Yixin Yang, et al.
Published: (2020-01-01)