Discriminant deep belief network for high-resolution SAR image classification
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- 作者：Zhiqiang Zhao ; zhq_zhao@yeah.net" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Licheng Jiao ; lcjiao@mail.xidian.edu.cn" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Jiaqi ZhaoAuthor Vitae ; Jing GuAuthor Vitae ; Jin ZhaoAuthor Vitae
- 关键词：Discriminant feature learning ; Deep belief network ; SAR image classification ; Ensemble learning ; Similarity measurement
- 刊名：Pattern Recognition
- 出版年：2017
- 出版时间：January 2017
- 年：2017
- 卷：61
- 期：Complete
- 页码：686-701
- 全文大小：6294 K
文摘
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A DisDBN is proposed to characterize SAR image patches in an unsupervised manner.
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Both the CPL and IPL are investigated to produce prototypes of SAR image patches.
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Some weak decision spaces are constructed based on the learned prototypes.
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A high-level feature is learned for the SAR image patch in a hierarchy manner.
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We show that our method can achieve a better classification performance.