Anomaly Detection of Hyperspectral Image With Hierarchical Antinoise Mutual-Incoherence- Induced Low-Rank Representation-Reference-Cited by-同舟云学术

Anomaly Detection of Hyperspectral Image With Hierarchical Antinoise Mutual-Incoherence- Induced Low-Rank Representation

Author:

Guo Tan¹^ORCID,He Long¹,Luo Fulin²^ORCID,Gong Xiuwen³^ORCID,Li Yuanyuan⁴^ORCID,Zhang Lei⁵^ORCID

Affiliation:

1. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China

2. College of Computer Science, Chongqing University, Chongqing, China

3. Faculty of Engineering, The University of Sydney, Camperdown, NSW, Australia

4. College of Automation, Chongqing University of Posts and Telecommunications, Chongqing, China

5. School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Chongqing

Key Scientific and Technological Innovation Project for “Chengdu-Chongqing Double City Economic Circle”

Macao Young Scholars Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

Reference43 articles.

Cited by 31 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

3. Spectral-Spatial Anomaly Detection in Hyperspectral Imagery Based on Dual-Domain Autoencoders;2024 13th Iranian/3rd International Machine Vision and Image Processing Conference (MVIP);2024-03-06