The invention discloses a polarization SAR image classification method based on a complex contour wave convolution neural network, and a problem of low classification accuracy in the prior art is mainly solved. The method comprises the steps of (1) inputting and normalizing a polarization coherent matrix T of a polarization SAR image to be classified, (2) according to the normalized matrix, constructing characteristic matrixes of a training data set and a test data set, (3) constructing a complex convolution neural network, and thus obtaining a complex contour wave convolution neural network, (4) training the complex contour wave convolution neural network by using the training data set, and obtaining a trained model, and (5) inputting the characteristic matrix of a test data set into the trained model to carry out classification, and obtaining a classification result. According to the method, the convolution neural network is extended to a complex domain to carry out operation and extract image characteristics of multiple scales, multiple directions and multiple resolution characteristics, the classification precision of the polarization SAR image is effectively improved, and the method can be used for target detection and identification.