Structural and Textural-Aware Feature Extraction for Hyperspectral Image Classification-Reference-Cited by-同舟云学术

Structural and Textural-Aware Feature Extraction for Hyperspectral Image Classification

Published:2024 Issue: Volume:21 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Zhang Ying¹^ORCID,Liang Lianhui²^ORCID,Li Jun³^ORCID,Plaza Antonio⁴^ORCID,Kang Xudong⁵^ORCID,Mao Jianxu²^ORCID,Wang Yaonan²^ORCID

Affiliation:

1. College of Railway Transportation, Hunan University of Technology, Zhuzhou, China

2. College of Electrical and Information Engineering, Hunan University, Changsha, China

3. Hubei Key Laboratory of Intelligent Geo-Information Processing, School of Computer Science, China University of Geosciences, Wuhan, China

4. Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Politecnica, University of Extremadura, Cáceres, Spain

5. School of Robotics, Hunan University, Changsha, China

Funder

Major Program of the National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/8859/10365397/10411886.pdf?arnumber=10411886

Reference12 articles.

1. Classification of hyperspectral data from urban areas based on extended morphological profiles

2. Intrinsic Image Decomposition for Feature Extraction of Hyperspectral Images

3. Two-Stage Hyperspectral Image Classification Using Few Labeled Samples

4. A Superpixel-Correlation-Based Multiview Approach for Hyperspectral Image Classification

5. Spectral–Spatial Hyperspectral Image Classification With Edge-Preserving Filtering

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