Anomaly Detection Based on Tree Topology for Hyperspectral Images-Reference-Cited by-同舟云学术

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Anomaly Detection Based on Tree Topology for Hyperspectral Images

Published:2023 Issue: Volume:16 Page:1985-2008
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Sun Xiaotong¹^ORCID,Zhang Bing²^ORCID,Zhuang Lina³^ORCID,Gao Hongmin¹^ORCID,Sun Xu³^ORCID,Ni Li³

Affiliation:

1. College of Computer and Information, Hohai University, Nanjing, China

2. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

3. Key Laboratory of Computational Optical Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

http://xplorestaging.ieee.org/ielx7/4609443/9973430/09852673.pdf?arnumber=9852673

Reference66 articles.

1. Closed-Form Nonparametric GLRT Detector for Subpixel Targets in Hyperspectral Images

2. Binary tree-inspired digital dendrimer

3. Hyperspectral Anomaly Detection by Fractional Fourier Entropy

4. EM algorithm for image segmentation initialized by a tree structure scheme

5. Efficient Hyperspectral Target Detection and Identification With Large Spectral Libraries

Cited by 3 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

1. Information Entropy Estimation Based on Point-Set Topology for Hyperspectral Anomaly Detection;IEEE Transactions on Geoscience and Remote Sensing;2024

2. Hyperspectral anomaly detection via weighted‐sparsity‐regularized tensor linear representation;IET Image Processing;2022-11-23

3. Kernel Minimum Noise Fraction Transformation-Based Background Separation Model for Hyperspectral Anomaly Detection;Remote Sensing;2022-10-15

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