Discriminant deep belief network for high-resolution SAR image classification
作者：
Highlights：
• A DisDBN is proposed to characterize SAR image patches in an unsupervised manner.
• Both the CPL and IPL are investigated to produce prototypes of SAR image patches.
• Some weak decision spaces are constructed based on the learned prototypes.
• A high-level feature is learned for the SAR image patch in a hierarchy manner.
• We show that our method can achieve a better classification performance.
摘要
Highlights•A DisDBN is proposed to characterize SAR image patches in an unsupervised manner.•Both the CPL and IPL are investigated to produce prototypes of SAR image patches.•Some weak decision spaces are constructed based on the learned prototypes.•A high-level feature is learned for the SAR image patch in a hierarchy manner.•We show that our method can achieve a better classification performance.
论文关键词：Discriminant feature learning,Deep belief network,SAR image classification,Ensemble learning,Similarity measurement
论文评审过程：Received 26 October 2015, Revised 19 May 2016, Accepted 24 May 2016, Available online 26 May 2016, Version of Record 13 October 2016.
论文官网地址：https://doi.org/10.1016/j.patcog.2016.05.028
