Terrain Classification of Polarimetric Synthetic Aperture Radar Images Based on Deep Learning and Conditional Random Field Model

Terrain Classification of Polarimetric Synthetic Aperture Radar Images Based on Deep Learning and Conditional Random Field Model

In recent years, Polarimetric Synthetic Aperture Radar (PolSAR) image classification has been investigated extensively. The traditional PolSAR image terrain classification methods result in a weak feature representation. To overcome this limitation, this study aims to propose a terrain classificatio...

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Bibliographic Details
Main Authors: HU Tao, LI Weihua, QIN Xianxiang, WANG Peng, YU Wangsheng, LI Jun
Format: Article
Language:English
Published: China Science Publishing & Media Ltd. (CSPM) 2019-08-01
Series:Leida xuebao
Subjects:
Polarimetric Synthetic Aperture Radar (PolSAR)
Terrain classification
Conditional Random Field (CRF)
Convolutional Neural Network (CNN)
Online Access:http://radars.ie.ac.cn/article/doi/10.12000/JR18065?viewType=HTML

Internet

http://radars.ie.ac.cn/article/doi/10.12000/JR18065?viewType=HTML

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