Polarimetric SAR Feature Extraction With Neighborhood Preservation-Based Deep Learning

Volume: 10, Issue: 4, Pages: 1456 - 1466
Published: Apr 1, 2017
Abstract
As an advanced nonlinear technique, deep learning, which is based on deep neural networks (DNNs), has attracted considerable attentions. In this paper, we propose a novel neighborhood preserved deep neural network (NPDNN) for polarimetric synthetic aperture radar feature extraction and classification. The spatial relation between pixels is exploited by a jointly weighting strategy. Not only the spatial neighbors but also the pixels in the same...
Paper Details
Title
Polarimetric SAR Feature Extraction With Neighborhood Preservation-Based Deep Learning
Published Date
Apr 1, 2017
Volume
10
Issue
4
Pages
1456 - 1466
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