Angle Distance-Based Hierarchical Background Separation Method for Hyperspectral Imagery Target Detection
Traditional detectors for hyperspectral imagery (HSI) target detection (TD) output the result after processing the HSI only once. However, using the prior target information only once is not sufficient, as it causes the inaccuracy of target extraction or the unclean separation of the background. In...
Main Authors: | Xiaohui Hao, Yiquan Wu, Peng Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-02-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/12/4/697 |
Similar Items
-
Background Learning Based on Target Suppression Constraint for Hyperspectral Target Detection
by: Weiying Xie, et al.
Published: (2020-01-01) -
Hierarchical Suppression Based Matched Filter for Hyperspertral Imagery Target Detection
by: Ce Gao, et al.
Published: (2021-12-01) -
Hierarchical Sub-Pixel Anomaly Detection Framework for Hyperspectral Imagery
by: Wenzheng Wang, et al.
Published: (2018-10-01) -
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) -
Hierarchical Structure-Based Noisy Labels Detection for Hyperspectral Image Classification
by: Bing Tu, et al.
Published: (2020-01-01)