Combined Conditional Random Fields Model for Supervised PolSAR Images Classification

Combined Conditional Random Fields Model for Supervised PolSAR Images Classification

More features and contextual information can be extracted and exploited to improve classification accuracy in complex Polarimetric Synthetic Aperture Radar (PolSAR) imagery classification. However, the problems of overfitting and feature interference caused by the increased high dimensions of featur...

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Bibliographic Details
Main Authors: Zou Huanxin, Luo Tiancheng, Zhang Yue, Zhou Shilin
Format: Article
Language:English
Published: China Science Publishing & Media Ltd. (CSPM) 2017-10-01
Series:Leida xuebao
Subjects:
Polarimetric Synthetic Aperture Radar (PolSAR)
Supervised classification
Conditional Random Fields (CRF)
Combined model
Online Access:http://radars.ie.ac.cn/fileup/HTML/R16109.htm

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