SAR image classification method based on contraction auto-encoders

The invention discloses an SAR (Synthetic Aperture Radar) image classification method based on contraction auto-encoders, comprising the steps of: (1) inputting an image; (2) performing stable wavelet decomposition; (3) selecting a training sample; (4) constructing two parallel levels of contraction auto-encoders; (5) training the two parallel levels of contraction auto-encoders; (6) constructing a sample feature set; (7) training a Softmax classifier; and (8) classifying. Compared with present feature extraction methods of multi-level local mode histograms, the SAR image classification method has the advantages of high classification precision, sound area consistency and accurate edge classification, solves the problems of speckle noise influence, area classification confusion and edge untidiness, and can be applied to SAR image object detection and object identification. 本发明公开了种基于收缩自动编码器的SAR图像分类方法。本发明实现的步骤为：(1)输入图像；(2)进行平稳小波分解；(3)选取训练样本；(4)构建并行的两层级的收缩自编码器；(5)训练并行的两层级的收缩自编器；(6)构造样本特征集；(7)训练Softmax分类器；(8)分类。本