Unsupervised Classification for Multilook Polarimetric SAR Images via Double Dirichlet Process Mixture Model-Reference-Cited by-同舟云学术

Unsupervised Classification for Multilook Polarimetric SAR Images via Double Dirichlet Process Mixture Model

Published:2024 Issue: Volume:62 Page:1-16
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Li Ze-Chen¹,Li Heng-Chao²^ORCID,Gao Gui³^ORCID,Hong Wen⁴,Emery William J.⁵

Affiliation:

1. School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China

2. School of Information Science and Technology and the National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu, China

3. Faculty of Geoscience and Environmental Engineering, Southwest Jiaotong University, Chengdu, China

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

5. Department of Aerospace Engineering Sciences, University of Colorado Boulder, Boulder, CO, USA

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10463089.pdf?arnumber=10463089

Reference54 articles.

1. A Radar Vegetation Index for Crop Monitoring Using Compact Polarimetric SAR Data

2. Ship Detection for Polarimetric SAR Images Based on $\mathcal {G}_p^0$ Mixture Model

3. A Two-Stage Method for Ship Detection Using PolSAR Image

4. Dynamic Fractal Texture Analysis for PolSAR Land Cover Classification

5. Unsupervised Land Cover/Land Use Classification Using PolSAR Imagery Based on Scattering Similarity

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