Bayesian Subpixel Mapping of Hyperspectral Imagery via Discrete Endmember Variability Mixture Model and Markov Random Field-Reference-Cited by-同舟云学术

Bayesian Subpixel Mapping of Hyperspectral Imagery via Discrete Endmember Variability Mixture Model and Markov Random Field

Published:2022 Issue: Volume:15 Page:6506-6517
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:

Chen Yujia¹^ORCID,Zhuo Rongming²,Xu Linlin¹^ORCID,Peng Junhuan¹,Qi Xiaoman¹^ORCID,Zhang Zhaoxu³^ORCID,Hu Zhongzheng⁴^ORCID

Affiliation:

1. School of Land Science and Technology, China University of Geosciences, Beijing, China

2. Aerospace Times FeiHong Technology Company Limited Beijing, China University of Geosciences, Beijing, China

3. School of Environmental Science and Engineering, Tiangong University, Tianjin, China

4. China Center for Resources Satellite Data and Application, China University of Geosciences, Beijing, China

Funder

National Natural Science Foundation of China

Ministry of Natural Resources of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

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