2023
DOI: 10.1117/1.jrs.17.034511
|View full text |Cite
|
Sign up to set email alerts
|

Prior-based collaborative representation with global adaptive weight for hyperspectral anomaly detection

Nan Wang,
Yuetian Shi,
Yinzhu Cheng
et al.

Abstract: Hyperspectral anomaly detection (HAD) is a technique to find observations without prior knowledge, which is of particular interest as a branch of remote sensing object detection. However, the application of HAD is limited by various challenges, such as high-dimensional data, high intraclass variability, redundant information, and limited samples. To overcome these restrictions, we report an unsupervised strategy to implement HAD by dimensionality reduction (DR) and prior-based collaborative representation with… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 41 publications
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?