New method of feature extraction in polarimetric SAR image classification

2002 ◽  
Author(s):  
Junyi Xu ◽  
Jian Yang ◽  
Ying-Ning Peng
Keyword(s):  
Feature Extraction ◽  
Image Classification ◽  
New Method ◽  
Sar Image ◽  
Polarimetric Sar

scholarly journals Polarimetric SAR image classification using 3D generative adversarial network

2021 ◽  
Vol 336 ◽  
pp. 08012
Author(s):  
Lu Liu ◽  
Guobao Feng
Keyword(s):  
Neural Network ◽  
Feature Extraction ◽  
Image Classification ◽  
Three Dimensional ◽  
Data Cube ◽  
Sar Image ◽  
Polarimetric Sar ◽  
Training Problem ◽  
Generative Adversarial Network ◽  
Adversarial Network

In this paper, a new architecture of three-dimensional deep convolutional generative adversarial network(3D-DCGAN) is specially defined to solve the unstable training problem of GAN and make full use of the information involved in polarimetric data. Firstly, a data cube with nine components of polarimetric coherency matrix are directly used as the input features of DCGAN. After that, a 3D convolutional model is designed as the components of generator and discriminator to construct the 3D-DCGAN, which considers the effective feature extraction capability of 3D convolutional neural network(CNN). Finally parameters of the network are fine-tuned to realize the polarimetric SAR image classification. The experiments results show the feasibility and efficiency of the proposed method.

Iteration Based Polarimetric SAR Image Classification

PIERS Online ◽  
2007 ◽  
Vol 3 (5) ◽  
pp. 625-628
Author(s):  
Jian Yang ◽  
Xiaoli She ◽  
Tao Xiong
Keyword(s):  
Image Classification ◽  
Sar Image ◽  
Polarimetric Sar
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